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Research papers
List of publications
2025
Pielat, Krystian; Grzonka, Daniel
Exploring Music Through AI: Predicting Popularity, Explicitness And Evolving Trends Proceedings Article
In: Scarpa, Marco; Cavalieri, Salvatore; Serrano, Salvatore; Vita, Fabrizio De (Ed.): ECMS 2025 : proceedings of the 39th ECMS International Conference on Modelling and Simulation, June 24th-June 27th, 2025, Catania, Italy, pp. 604-612, European Council for Modelling and Simulation – ECMS, 2025, ISSN: 2522-2422.
Abstract | Links | BibTeX | Tags:
@inproceedings{Pielat2025,
title = {Exploring Music Through AI: Predicting Popularity, Explicitness And Evolving Trends},
author = {Krystian Pielat and Daniel Grzonka},
editor = {Marco Scarpa and Salvatore Cavalieri and Salvatore Serrano and Fabrizio De Vita},
url = {https://www.scs-europe.net/dlib/2025/2025-0604.html},
doi = {10.7148/2025-0604},
issn = {2522-2422},
year = {2025},
date = {2025-06-24},
urldate = {2025-06-24},
booktitle = {ECMS 2025 : proceedings of the 39th ECMS International Conference on Modelling and Simulation, June 24th-June 27th, 2025, Catania, Italy},
volume = {39},
issue = {1},
pages = {604-612},
publisher = {European Council for Modelling and Simulation \textendash ECMS},
series = {Communications of the ECMS},
abstract = {This paper uses advanced data analysis and artificial intelligence methods to explore the relationships between metadata, lyrics and acoustic characteristics of music tracks. It creates a diverse dataset of songs consisting of audio features, lyrics and MP3 tracks. It uses a well-defined data collection methodology to study patterns and interactions related to song popularity, explicitness, genre identity and other song characteristics. This study also examines how these properties evolve. It aims to uncover hidden patterns and understand interactions present in the collected data using thorough exploratory data analysis, comprehensive feature engineering, natural language processing, machine learning techniques, and statistical methods.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper uses advanced data analysis and artificial intelligence methods to explore the relationships between metadata, lyrics and acoustic characteristics of music tracks. It creates a diverse dataset of songs consisting of audio features, lyrics and MP3 tracks. It uses a well-defined data collection methodology to study patterns and interactions related to song popularity, explicitness, genre identity and other song characteristics. This study also examines how these properties evolve. It aims to uncover hidden patterns and understand interactions present in the collected data using thorough exploratory data analysis, comprehensive feature engineering, natural language processing, machine learning techniques, and statistical methods.
Aqeel, Sehrish; Khan, Adnan Shahid; Abbasi, Irshad Ahmed; Algarni, Fahad; Grzonka, Daniel
Enhancing IoT security with a DNA-based lightweight cryptography system Journal Article
In: Scientific Reports, vol. 15, no. 13367, 2025, ISSN: 2045-2322.
Abstract | Links | BibTeX | Tags:
@article{Aqeel2025,
title = {Enhancing IoT security with a DNA-based lightweight cryptography system},
author = {Sehrish Aqeel and Adnan Shahid Khan and Irshad Ahmed Abbasi and Fahad Algarni and Daniel Grzonka},
url = {https://www.nature.com/articles/s41598-025-96292-0},
doi = {10.1038/s41598-025-96292-0},
issn = {2045-2322},
year = {2025},
date = {2025-04-17},
urldate = {2025-12-00},
journal = {Scientific Reports},
volume = {15},
number = {13367},
publisher = {Springer Science and Business Media LLC},
abstract = {The rapid increase of internet of things (IoT) devices in our daily lives has highlighted the critical need for strong security measures to protect the integrity and confidentiality of IoT communications. This paper presents a novel solution to this growing problem using a secure and lightweight DNA-based encryption method, elliptic curve encryption (ECC), to secure IoT communications. The research explains how DNA-LWCS (DNA-based lightweight cryptography system) utilizes basic encryption methods to secure data transmission against system complexity while maintaining security effectiveness. The security key ensures enough protection for achieving the necessary level of confidentiality. Three fundamental keys are extracted from publicly accessible DNA sequences to start the procedure during its first phase. When employed together with ECC these keys generate a private key during the second stage of development. During the second stage the keys generate a private key based on ECC (elliptic curve cryptography) protocol. The encryption and decryption of IoT device messages requires this private key during the last operational phase. The combination of intuitive DNA sequences together with ECC generates better security and decreases the strain on systems. Practical evaluations demonstrate that the proposed encryption method offers better security and efficiency compared to existing methods while maintaining weightless operational performance. This makes it an ideal solution to secure IoT data exchange. The encryption method we investigated received detailed study which focused on both security and efficiency criteria during our research timeframe. The research demonstrates our security method outperforms other solutions by maintaining low resource requirements. Our proposed DNA-based encryption system shows potential as a suitable security measure for protecting IoT connections through its lightweight design capabilities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rapid increase of internet of things (IoT) devices in our daily lives has highlighted the critical need for strong security measures to protect the integrity and confidentiality of IoT communications. This paper presents a novel solution to this growing problem using a secure and lightweight DNA-based encryption method, elliptic curve encryption (ECC), to secure IoT communications. The research explains how DNA-LWCS (DNA-based lightweight cryptography system) utilizes basic encryption methods to secure data transmission against system complexity while maintaining security effectiveness. The security key ensures enough protection for achieving the necessary level of confidentiality. Three fundamental keys are extracted from publicly accessible DNA sequences to start the procedure during its first phase. When employed together with ECC these keys generate a private key during the second stage of development. During the second stage the keys generate a private key based on ECC (elliptic curve cryptography) protocol. The encryption and decryption of IoT device messages requires this private key during the last operational phase. The combination of intuitive DNA sequences together with ECC generates better security and decreases the strain on systems. Practical evaluations demonstrate that the proposed encryption method offers better security and efficiency compared to existing methods while maintaining weightless operational performance. This makes it an ideal solution to secure IoT data exchange. The encryption method we investigated received detailed study which focused on both security and efficiency criteria during our research timeframe. The research demonstrates our security method outperforms other solutions by maintaining low resource requirements. Our proposed DNA-based encryption system shows potential as a suitable security measure for protecting IoT connections through its lightweight design capabilities.
Johari, Mohammad Firdaus; Chiew, Kang Leng; Hosen, Abdul Razak; Yong, Kelvin S. C.; Khan, Adnan Shahid; Abbasi, Irshad Ahmed; Grzonka, Daniel
Key insights into recommended SMS spam detection datasets Journal Article
In: Scientific Reports, vol. 15, no. 8162, 2025, ISSN: 2045-2322.
Abstract | Links | BibTeX | Tags:
@article{Johari2025,
title = {Key insights into recommended SMS spam detection datasets},
author = {Mohammad Firdaus Johari and Kang Leng Chiew and Abdul Razak Hosen and Kelvin S.C. Yong and Adnan Shahid Khan and Irshad Ahmed Abbasi and Daniel Grzonka},
url = {https://www.nature.com/articles/s41598-025-92223-1},
doi = {10.1038/s41598-025-92223-1},
issn = {2045-2322},
year = {2025},
date = {2025-03-10},
journal = {Scientific Reports},
volume = {15},
number = {8162},
publisher = {Springer Science and Business Media LLC},
abstract = {Short Message Service (SMS) spam poses significant risks, including financial scams and phishing attempts. Although numerous datasets from online repositories have been utilized to address this issue, little attention has been given to evaluating their effectiveness and impact on SMS spam detection models. This study fills this gap by assessing the performance of ten SMS spam detection datasets using Decision Tree and Multinomial Na\"{i}ve Bayes models. Datasets were evaluated based on accuracy and qualitative factors such as authenticity, class imbalance, feature diversity, metadata availability, and preprocessing needs. Due to the multilingual nature of the datasets, experiments were conducted with two stopword removal groups: one in English and another in the respective non-English languages. The key findings of this research have led to the recommendation of Dataset 5 for future SMS spam detection research, as evidence from the dataset’s high qualitative assessment score of 3.8 out of 5.0 due to its high feature diversity, real-world complexity, and balanced class distribution, and low detection rate of 86.10% from Multinomial Na\"{i}ve Bayes. Recommending a dataset that poses challenges for high model performance fosters the development of more robust and adaptable spam detection models capable of handling diverse forms of noise and ambiguity. Furthermore, selecting the dataset with the highest qualitative score enhances research quality, improves model generalizability, and mitigates risks related to bias and inconsistencies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Short Message Service (SMS) spam poses significant risks, including financial scams and phishing attempts. Although numerous datasets from online repositories have been utilized to address this issue, little attention has been given to evaluating their effectiveness and impact on SMS spam detection models. This study fills this gap by assessing the performance of ten SMS spam detection datasets using Decision Tree and Multinomial Naïve Bayes models. Datasets were evaluated based on accuracy and qualitative factors such as authenticity, class imbalance, feature diversity, metadata availability, and preprocessing needs. Due to the multilingual nature of the datasets, experiments were conducted with two stopword removal groups: one in English and another in the respective non-English languages. The key findings of this research have led to the recommendation of Dataset 5 for future SMS spam detection research, as evidence from the dataset’s high qualitative assessment score of 3.8 out of 5.0 due to its high feature diversity, real-world complexity, and balanced class distribution, and low detection rate of 86.10% from Multinomial Naïve Bayes. Recommending a dataset that poses challenges for high model performance fosters the development of more robust and adaptable spam detection models capable of handling diverse forms of noise and ambiguity. Furthermore, selecting the dataset with the highest qualitative score enhances research quality, improves model generalizability, and mitigates risks related to bias and inconsistencies.
2024
Nguyen, Ha Huy Cuong; Grzonka, Daniel; Khoa, Bui Thanh; Sagar, Ketaraju Venkata Daya; Abbasi, Irshad Ahmed; Mahaveerakannan, R.; Alkhayyat, Ahmed
New trends in over the top media service (OTT) web user behaviour analysis and unethical user prediction Journal Article
In: Mobile Networks and Applications : the journal of special issues on mobility of systems, users, data and computing, vol. 29, no. Article in press, pp. 1811–1827, 2024, ISSN: 1572-8153.
Abstract | Links | BibTeX | Tags:
@article{bpk99442,
title = {New trends in over the top media service (OTT) web user behaviour analysis and unethical user prediction},
author = {Ha Huy Cuong Nguyen and Daniel Grzonka and Bui Thanh Khoa and Ketaraju Venkata Daya Sagar and Irshad Ahmed Abbasi and R. Mahaveerakannan and Ahmed Alkhayyat},
url = {https://link.springer.com/article/10.1007/s11036-023-02214-7},
doi = {10.1007/s11036-023-02214-7},
issn = {1572-8153},
year = {2024},
date = {2024-12-31},
urldate = {2024-12-31},
journal = {Mobile Networks and Applications : the journal of special issues on mobility of systems, users, data and computing},
volume = {29},
number = {Article in press},
pages = {1811\textendash1827},
abstract = {This research shows unethical user prediction on the peer-to-peer content delivery network against the Over-The-Top media service (OTT). The Web User Behaviour Analysis and unethical user prediction are performed based on the OTT multimedia service platform. The Analysis and unethical user prediction contain the four stages of processing. Firstly "Peer to Peer Content Delivery Network" is used to provide services and ideal resources (User). It uses ResourceCache: an optimized algorithm for giving efcient CDN-based over-the-top video streaming services. Secondly, “Selective destination Bitrateadaptivity” is employed to provide the OTT Service (Devices). It utilizes bitrate adaptivity to improve the adaptivity of Over-The-Top Television systems. Thirdly, the “Network Functions Virtualization (NFV)” enabled multi-access edge data centers to embed to maintain sufcient data about users and their respective devices. It uses the QoE-based Load Balancing of OTT video content in CDN networks to improve the QoE of OTT multimedia services in wireless scenarios. Finally, the efcient “Review of Recommender System” are taken to collect feedback about services and subscription. It is most useful to check unethical user access. The performance result of the proposed system conceives the analysis based on web users\' behavior prediction accuracy of 76%, Average precision of 67.8%, Average recall of 74.2%, and Average f1-measures of 85.9% against the performance of unethical user prediction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This research shows unethical user prediction on the peer-to-peer content delivery network against the Over-The-Top media service (OTT). The Web User Behaviour Analysis and unethical user prediction are performed based on the OTT multimedia service platform. The Analysis and unethical user prediction contain the four stages of processing. Firstly "Peer to Peer Content Delivery Network" is used to provide services and ideal resources (User). It uses ResourceCache: an optimized algorithm for giving efcient CDN-based over-the-top video streaming services. Secondly, “Selective destination Bitrateadaptivity” is employed to provide the OTT Service (Devices). It utilizes bitrate adaptivity to improve the adaptivity of Over-The-Top Television systems. Thirdly, the “Network Functions Virtualization (NFV)” enabled multi-access edge data centers to embed to maintain sufcient data about users and their respective devices. It uses the QoE-based Load Balancing of OTT video content in CDN networks to improve the QoE of OTT multimedia services in wireless scenarios. Finally, the efcient “Review of Recommender System” are taken to collect feedback about services and subscription. It is most useful to check unethical user access. The performance result of the proposed system conceives the analysis based on web users' behavior prediction accuracy of 76%, Average precision of 67.8%, Average recall of 74.2%, and Average f1-measures of 85.9% against the performance of unethical user prediction.
Mityushev, Vladimir; Grzonka, Daniel
Intersections among cluster inclusions in multi-phase polydispersed structures Proceedings Article
In: Grzonka, Daniel; Rylko, Natalia; Suchacka, Grazyna; Mityushev, Vladimir (Ed.): ECMS 2024 : proceedings of the 38th ECMS International Conference on Modelling and Simulation, June 4th-June 7th, 2024 Cracow, Poland, pp. 295–303, ECMS, 2024, ISBN: 978-3-937436-84-5.
Abstract | Links | BibTeX | Tags:
@inproceedings{Mityushev2024,
title = {Intersections among cluster inclusions in multi-phase polydispersed structures},
author = {Vladimir Mityushev and Daniel Grzonka},
editor = {Daniel Grzonka and Natalia Rylko and Grazyna Suchacka and Vladimir Mityushev},
doi = {10.7148/2024-0295},
isbn = {978-3-937436-84-5},
year = {2024},
date = {2024-06-00},
urldate = {2024-06-07},
booktitle = {ECMS 2024 : proceedings of the 38th ECMS International Conference on Modelling and Simulation, June 4th-June 7th, 2024 Cracow, Poland},
pages = {295--303},
publisher = {ECMS},
abstract = {This paper introduces a novel approach inspired by structural sums, which describes the interactions among inclusions of dispersed composites. These sums serve as the cornerstone for mathematical models of random structures within the framework of the theory of analytical representative volume element (aRVE). We quantified the inter-phase interactions within composites based on the methodological aspects presented.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper introduces a novel approach inspired by structural sums, which describes the interactions among inclusions of dispersed composites. These sums serve as the cornerstone for mathematical models of random structures within the framework of the theory of analytical representative volume element (aRVE). We quantified the inter-phase interactions within composites based on the methodological aspects presented.
Grzonka, Daniel; Rylko, Natalia; Suchacka, Grazyna; Mityushev, Vladimir (Ed.)
Proceedings of the 38th ECMS International Conference on Modelling and Simulation Proceedings
European Council for Modelling and Simulation, vol. 38, 2024, ISBN: 978-3-937436-84-5.
Abstract | Links | BibTeX | Tags:
@proceedings{Grzonka2024,
title = {Proceedings of the 38th ECMS International Conference on Modelling and Simulation},
editor = {Daniel Grzonka and Natalia Rylko and Grazyna Suchacka and Vladimir Mityushev},
url = {https://scs-europe.net/conf/ecms2024/ecms2024proceedings.pdf},
doi = {10.7148/2024},
isbn = {978-3-937436-84-5},
year = {2024},
date = {2024-06-00},
urldate = {2024-06-00},
booktitle = {Communications of the ECMS},
issuetitle = {Proceedings of the 38th ECMS International Conference on Modelling and Simulation},
volume = {38},
issue = {1},
pages = {622},
publisher = {European Council for Modelling and Simulation},
abstract = {This is the 38th time that, under the umbrella of the ECMS International Conference on Modelling and Simulation, vibrant and experienced young and enthusiastic scientists from all over the world have gathered around the two pillars of modelling and simulation to present the results of their scientific research.
This year\'s edition is organised by the esteemed Faculty of Computer Science and Telecommunications of the Cracow University of Technology (PK), commemorating its 25th anniversary in 2024. Tadeusz Ko\'{s}ciuszko Cracow University of Technology has, for almost 80 years, embodied a rich tradition, modern education methods, and innovative research. The university offers full-time and part-time undergraduate and postgraduate education, as well as Doctoral School and postgraduate studies. The Polytechnic\'s educational offer includes more than 30 fields of study, delivered at eight faculties. Nearly 14,000 students take courses, and nearly 1,100 academic teachers oversee their education. The total number of alumni who graduated from PK has exceeded 80,000. The Faculty of Computer Science and Telecommunications, recognised as one of the top three research institutions in Poland from 2017 to 2021, is proud of receiving the highest grade (A) in the scientific discipline of Information and Communication Technologies. Collaborations with universities and research hubs globally foster joint research ventures, student exchanges, and the pursuit of additional certifications.
This year\'s conference takes place from 4 to 7 June 2024 in Cracow, Poland. During the sessions organised in nine tracks, 79 high-quality peer-reviewed scientific papers are presented. The conference showcases advanced computational and simulation methods applied to engineering, economic, and industrial problems, highlighting the growing role of digital technologies in scientific and technological progress and their impact on socio-economic aspects of life.
Special talks are given by world-renowned scholars, Prof. Stanis\law Dro\.{z}d\.{z} and Prof. Vil\'{e}m Nov\'{a}k. The topic of Prof. Stanis\law Dro\.{z}d\.{z}’s keynote speech is "Complex systems approach to natural language." Prof. Vil\'{e}m Nov\'{a}k presents the results of his work under the topic "Formal theory of quantifiers in natural language and their syllogisms."
We thank all participants for submitting papers, invited keynote speakers for their talks, track chairs for managing the editorial process, IPC members for reviewing papers, and local organisers for their invaluable contributions. We thank the ECMS President, Prof. Mauro Iacono, for choosing Cracow as the venue for the event, as well as the Council members for their excellent work. Special appreciation is reserved for Martina Maria Seidel for her meticulous orchestration of the conference logistics.},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
This is the 38th time that, under the umbrella of the ECMS International Conference on Modelling and Simulation, vibrant and experienced young and enthusiastic scientists from all over the world have gathered around the two pillars of modelling and simulation to present the results of their scientific research.
This year's edition is organised by the esteemed Faculty of Computer Science and Telecommunications of the Cracow University of Technology (PK), commemorating its 25th anniversary in 2024. Tadeusz Kościuszko Cracow University of Technology has, for almost 80 years, embodied a rich tradition, modern education methods, and innovative research. The university offers full-time and part-time undergraduate and postgraduate education, as well as Doctoral School and postgraduate studies. The Polytechnic's educational offer includes more than 30 fields of study, delivered at eight faculties. Nearly 14,000 students take courses, and nearly 1,100 academic teachers oversee their education. The total number of alumni who graduated from PK has exceeded 80,000. The Faculty of Computer Science and Telecommunications, recognised as one of the top three research institutions in Poland from 2017 to 2021, is proud of receiving the highest grade (A) in the scientific discipline of Information and Communication Technologies. Collaborations with universities and research hubs globally foster joint research ventures, student exchanges, and the pursuit of additional certifications.
This year's conference takes place from 4 to 7 June 2024 in Cracow, Poland. During the sessions organised in nine tracks, 79 high-quality peer-reviewed scientific papers are presented. The conference showcases advanced computational and simulation methods applied to engineering, economic, and industrial problems, highlighting the growing role of digital technologies in scientific and technological progress and their impact on socio-economic aspects of life.
Special talks are given by world-renowned scholars, Prof. Stanisław Drożdż and Prof. Vilém Novák. The topic of Prof. Stanisław Drożdż’s keynote speech is "Complex systems approach to natural language." Prof. Vilém Novák presents the results of his work under the topic "Formal theory of quantifiers in natural language and their syllogisms."
We thank all participants for submitting papers, invited keynote speakers for their talks, track chairs for managing the editorial process, IPC members for reviewing papers, and local organisers for their invaluable contributions. We thank the ECMS President, Prof. Mauro Iacono, for choosing Cracow as the venue for the event, as well as the Council members for their excellent work. Special appreciation is reserved for Martina Maria Seidel for her meticulous orchestration of the conference logistics.
This year's edition is organised by the esteemed Faculty of Computer Science and Telecommunications of the Cracow University of Technology (PK), commemorating its 25th anniversary in 2024. Tadeusz Kościuszko Cracow University of Technology has, for almost 80 years, embodied a rich tradition, modern education methods, and innovative research. The university offers full-time and part-time undergraduate and postgraduate education, as well as Doctoral School and postgraduate studies. The Polytechnic's educational offer includes more than 30 fields of study, delivered at eight faculties. Nearly 14,000 students take courses, and nearly 1,100 academic teachers oversee their education. The total number of alumni who graduated from PK has exceeded 80,000. The Faculty of Computer Science and Telecommunications, recognised as one of the top three research institutions in Poland from 2017 to 2021, is proud of receiving the highest grade (A) in the scientific discipline of Information and Communication Technologies. Collaborations with universities and research hubs globally foster joint research ventures, student exchanges, and the pursuit of additional certifications.
This year's conference takes place from 4 to 7 June 2024 in Cracow, Poland. During the sessions organised in nine tracks, 79 high-quality peer-reviewed scientific papers are presented. The conference showcases advanced computational and simulation methods applied to engineering, economic, and industrial problems, highlighting the growing role of digital technologies in scientific and technological progress and their impact on socio-economic aspects of life.
Special talks are given by world-renowned scholars, Prof. Stanisław Drożdż and Prof. Vilém Novák. The topic of Prof. Stanisław Drożdż’s keynote speech is "Complex systems approach to natural language." Prof. Vilém Novák presents the results of his work under the topic "Formal theory of quantifiers in natural language and their syllogisms."
We thank all participants for submitting papers, invited keynote speakers for their talks, track chairs for managing the editorial process, IPC members for reviewing papers, and local organisers for their invaluable contributions. We thank the ECMS President, Prof. Mauro Iacono, for choosing Cracow as the venue for the event, as well as the Council members for their excellent work. Special appreciation is reserved for Martina Maria Seidel for her meticulous orchestration of the conference logistics.
2023
Grzonka, Daniel; Swałdek, Krzysztof; Abbasi, Irshad Ahmed; Sagar, Ketaraju Venkata Daya
The impact of the AI revolution on the ICT labour market Journal Article
In: Edukacja Biologiczna i Środowiskowa, vol. 80, iss. 2, pp. 65-84, 2023, ISSN: 2720-5789.
Abstract | Links | BibTeX | Tags:
@article{2023,
title = {The impact of the AI revolution on the ICT labour market},
author = { Daniel Grzonka and Krzysztof Swa\ldek and Irshad Ahmed Abbasi and Ketaraju Venkata Daya Sagar},
url = {https://ibe.edu.pl/images/EBiS/Numery/2023-2/EBiS-2023-2-4-The-impact-of-the-AI-revolution.pdf},
doi = {10.24131/3247.230204},
issn = {2720-5789},
year = {2023},
date = {2023-12-31},
urldate = {2023-00-00},
journal = {Edukacja Biologiczna i \'{S}rodowiskowa},
volume = {80},
issue = {2},
pages = {65-84},
publisher = {Instytut Bada\'{n} Edukacyjnych},
abstract = {Artificial intelligence evolves in cyclical patterns, with phases of dynamic technical progress, referred to as “AI springs”, interspersed with periods of stagnation, called “AI winters”. The current phase, known not only as another “AI spring” but rather as an “AI revolution”, has accelerated particularly over the past year, starting with the launch of the ChatGPT service on November 30, 2022. The widespread adoption of generative AI systems has significantly impacted numerous aspects of socio-economic life, with a particular focus on the ICT sector. This paper presents a detailed and comprehensive analysis of the labour market, utilising quantitative and qualitative data, to assess the impact of artificial intelligence tools, including their effects on the IT industry, potential AI applications across various sectors of the global economy, and a detailed study of the transformation of the Polish labour market in terms of AI-related occupations. In addition, the challenges facing the higher education system due to the growing demand for specialised personnel in artificial intelligence are identified. The paper also attempts to evaluate future trends in the labour market relating to the further development of artificial intelligence, with a particular focus on potential changes in the demand for competencies and possible challenges faced by various sectors of the economy.
},
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pubstate = {published},
tppubtype = {article}
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Artificial intelligence evolves in cyclical patterns, with phases of dynamic technical progress, referred to as “AI springs”, interspersed with periods of stagnation, called “AI winters”. The current phase, known not only as another “AI spring” but rather as an “AI revolution”, has accelerated particularly over the past year, starting with the launch of the ChatGPT service on November 30, 2022. The widespread adoption of generative AI systems has significantly impacted numerous aspects of socio-economic life, with a particular focus on the ICT sector. This paper presents a detailed and comprehensive analysis of the labour market, utilising quantitative and qualitative data, to assess the impact of artificial intelligence tools, including their effects on the IT industry, potential AI applications across various sectors of the global economy, and a detailed study of the transformation of the Polish labour market in terms of AI-related occupations. In addition, the challenges facing the higher education system due to the growing demand for specialised personnel in artificial intelligence are identified. The paper also attempts to evaluate future trends in the labour market relating to the further development of artificial intelligence, with a particular focus on potential changes in the demand for competencies and possible challenges faced by various sectors of the economy.
Mycek, Andrzej; Grzonka, Daniel; Tchórzewski, Jacek
Agent-based Simulation and analysis of Infrastructure-as-Code process to build and manage cloud environment Proceedings Article
In: Vicario, Enrico; Bandinelli, Romeo; Fani, Virginia; Mastroianni, Michele (Ed.): ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th – June 23rd, 2023 Florence, Italy, pp. 513-520, ECMS, Caserta, 2023, ISSN: 2522-2422.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk98477,
title = {Agent-based Simulation and analysis of Infrastructure-as-Code process to build and manage cloud environment},
author = {Andrzej Mycek and Daniel Grzonka and Jacek Tch\'{o}rzewski},
editor = {Enrico Vicario and Romeo Bandinelli and Virginia Fani and Michele Mastroianni},
url = {https://www.grzonka.eu/?attachment_id=363},
doi = {10.7148/2023-0513},
issn = {2522-2422},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th \textendash June 23rd, 2023 Florence, Italy},
volume = {37},
number = {1},
pages = {513-520},
publisher = {ECMS},
address = {Caserta},
series = {Communications of the ECMS},
abstract = {Widespread cloud systems present new challenges time and time again. An essential element of such environments is their management. The Infrastructure as Code model has been gaining popularity for some time. In work presented here, we have proposed an agent-based approach to process execution within the Infrastructure as Code approach and have performed several numerical experiments. The work also includes an original formal agent model of the system. The results obtained allow us to develop trade-offs regarding computational demand and utilization.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Widespread cloud systems present new challenges time and time again. An essential element of such environments is their management. The Infrastructure as Code model has been gaining popularity for some time. In work presented here, we have proposed an agent-based approach to process execution within the Infrastructure as Code approach and have performed several numerical experiments. The work also includes an original formal agent model of the system. The results obtained allow us to develop trade-offs regarding computational demand and utilization.
2022
Sośnicki, Adrian; Grzonka, Daniel; Gaża, Łukasz
Agent and evolutionary-based modelling and simulation of a simplified living system Proceedings Article
In: Hameed, Ibrahim A.; Hasan, Agus; Alaliyat, Saleh Abdel-Afou (Ed.): ECMS 2022 : proceedings of the 36th ECMS International Conference on Modelling and Simulation, May 30th – June 3rd, 2022 Ålesund, Norway, pp. 296-302, European Council for Modelling and Simulation, Sbr.-Dudweiler, 2022, ISSN: 2522-2422.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk96345,
title = {Agent and evolutionary-based modelling and simulation of a simplified living system},
author = {Adrian So\'{s}nicki and Daniel Grzonka and \Lukasz Ga\.{z}a},
editor = {Ibrahim A. Hameed and Agus Hasan and Saleh Abdel-Afou Alaliyat},
url = {http://www.scs-europe.net/dlib/2022/ecms2022acceptedpapers/0296_dis_ecms2022_0065.pdf},
doi = {10.7148/2022-0296},
issn = {2522-2422},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {ECMS 2022 : proceedings of the 36th ECMS International Conference on Modelling and Simulation, May 30th \textendash June 3rd, 2022 r{A}lesund, Norway},
volume = {36},
number = {1},
pages = {296-302},
publisher = {European Council for Modelling and Simulation},
address = {Sbr.-Dudweiler},
series = {Communications of the ECMS},
abstract = {Modelling artificial life has been an issue explored for several decades. However, science continues to surprise us with novel approaches to this problem. The aim of this paper is to innovative model a simplified living environment based on the agent paradigm and genetic algorithms. This paper also proposes a novel way of defining agent systems and artificial life embedded in a genetic approach. In the modelled and implemented environment there is one species of fauna and a simple species of flora that serves as food for the fauna. The fauna is implemented using agents inscribed in a genetic representation. The experimental part of the work includes calls to the simulator and the study of the dependencies resulting from the simulation mechanisms.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Modelling artificial life has been an issue explored for several decades. However, science continues to surprise us with novel approaches to this problem. The aim of this paper is to innovative model a simplified living environment based on the agent paradigm and genetic algorithms. This paper also proposes a novel way of defining agent systems and artificial life embedded in a genetic approach. In the modelled and implemented environment there is one species of fauna and a simple species of flora that serves as food for the fauna. The fauna is implemented using agents inscribed in a genetic representation. The experimental part of the work includes calls to the simulator and the study of the dependencies resulting from the simulation mechanisms.
Kołodziej, Joanna; Hopmann, Cornelio; Coppa, Giovanni; Grzonka, Daniel; Widłak, Adrian
Intelligent transportation systems – models, challenges, security aspects Book Chapter
In: Kołodziej, Joanna; Repetto, Matteo; Duzha, Armend (Ed.): Cybersecurity of digital service chains : challenges, methodologies, and tools, vol. 13300, pp. 56-82, Springer, Cham, 2022, ISBN: 978-3-031-04036-8.
Abstract | Links | BibTeX | Tags:
@inbook{bpk96084,
title = {Intelligent transportation systems \textendash models, challenges, security aspects},
author = {Joanna Ko\lodziej and Cornelio Hopmann and Giovanni Coppa and Daniel Grzonka and Adrian Wid\lak},
editor = {Joanna Ko\lodziej and Matteo Repetto and Armend Duzha},
url = {https://link.springer.com/chapter/10.1007/978-3-031-04036-8_3},
doi = {10.1007/978-3-031-04036-8_3},
isbn = {978-3-031-04036-8},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Cybersecurity of digital service chains : challenges, methodologies, and tools},
volume = {13300},
pages = {56-82},
publisher = {Springer},
address = {Cham},
series = {Lecture Notes in Computer Science},
abstract = {As cars and other transportation devices become increasingly interconnected, mobility takes on a new meaning, offering new opportunities. The integration of new communications technologies in modern vehicles has generated an enormous variety of data from various communications sources. Hence, there is a demand for inteligent transportation systems that can provide safe and reliable transportation while maintaining environmental conditions such as pollution, CO2 emission, and energy consumption. This chapter provides an overview of the Intelligent Transportation Systems (ITS) models. Briefly, it discusses the most important features of the systems and challenges, mostly related to the security in data and information processing. Fast anomalies detection and prevention of external attacks may help solve the problems of traffic congestion and road safety to prevent accidents. The chapter contains the description of the realistic Smart Transportation System developed by the Wobcom company and implemented in Wolfsburg (Germany). That system is also used for practical validation of the security service components of the platform created in the GUARD project.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
As cars and other transportation devices become increasingly interconnected, mobility takes on a new meaning, offering new opportunities. The integration of new communications technologies in modern vehicles has generated an enormous variety of data from various communications sources. Hence, there is a demand for inteligent transportation systems that can provide safe and reliable transportation while maintaining environmental conditions such as pollution, CO2 emission, and energy consumption. This chapter provides an overview of the Intelligent Transportation Systems (ITS) models. Briefly, it discusses the most important features of the systems and challenges, mostly related to the security in data and information processing. Fast anomalies detection and prevention of external attacks may help solve the problems of traffic congestion and road safety to prevent accidents. The chapter contains the description of the realistic Smart Transportation System developed by the Wobcom company and implemented in Wolfsburg (Germany). That system is also used for practical validation of the security service components of the platform created in the GUARD project.
2021
Wilczyński, Andrzej; Kołodziej, Joanna; Grzonka, Daniel
Security aspects in blockchain-based scheduling in mobile multi-cloud computing Proceedings Article
In: Lefevre, Laurent; Patterson, Stacy; Lee, Young Choon; Shen, Haiying; Ilager, Shashikant; Goudarzi, Mohammad; Toosi, Adel N.; Buyya, Rajkumar (Ed.): CCGrid 2021 : 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, 10-13 May 2021 Melbourne, Australia : proceedings, pp. 696-703, IEEE, Los Alamitos [etc.], 2021, ISBN: 978-1-7281-9586-5.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk94325,
title = {Security aspects in blockchain-based scheduling in mobile multi-cloud computing},
author = {Andrzej Wilczy\'{n}ski and Joanna Ko\lodziej and Daniel Grzonka},
editor = {Laurent Lefevre and Stacy Patterson and Young Choon Lee and Haiying Shen and Shashikant Ilager and Mohammad Goudarzi and Adel N. Toosi and Rajkumar Buyya},
url = {https://ieeexplore.ieee.org/document/9499350},
doi = {10.1109/CCGrid51090.2021.00084},
isbn = {978-1-7281-9586-5},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {CCGrid 2021 : 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, 10-13 May 2021 Melbourne, Australia : proceedings},
pages = {696-703},
publisher = {IEEE},
address = {Los Alamitos [etc.]},
abstract = {The intensive development and growth in the popularity of mobile cloud computing services bring a critical need to introduce new solutions that increase the level of cloud and users security. One of the critical issues in highly distributed computational systems is a task scheduling process. This process may be exposed to many external and internal security threats, like task injection, machine failure or generation of incorrect schedule. These problems are especially important in mobile environments. It can be even more complicated if we take into consideration the personalization of the services offered. Recently, blockchain has been gaining rapidly in popularity, combining high efficiency with applications in distributed and highly personalized computational environments. In this paper, we developed and described a novel model for security-aware task scheduling in cloud computing based on blockchain technology. Unlike other blockchain-based solutions, the proposed model uses Proof of Stake, which does not have high requirements for computing power. A series of conducted experiments confirmed the high efficiency of the proposed model.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The intensive development and growth in the popularity of mobile cloud computing services bring a critical need to introduce new solutions that increase the level of cloud and users security. One of the critical issues in highly distributed computational systems is a task scheduling process. This process may be exposed to many external and internal security threats, like task injection, machine failure or generation of incorrect schedule. These problems are especially important in mobile environments. It can be even more complicated if we take into consideration the personalization of the services offered. Recently, blockchain has been gaining rapidly in popularity, combining high efficiency with applications in distributed and highly personalized computational environments. In this paper, we developed and described a novel model for security-aware task scheduling in cloud computing based on blockchain technology. Unlike other blockchain-based solutions, the proposed model uses Proof of Stake, which does not have high requirements for computing power. A series of conducted experiments confirmed the high efficiency of the proposed model.
2020
Holvitie, Johannes; Jaakola, Mikko; Polvinen, Tuisku; Käyhkö, Niina; Inca, Carlos Gonzales; Kisielewicz, Paweł; Grzonka, Daniel; Widłak, Adrian; Szuster, Piotr; Kołodziej, Joanna; Główczyk, Dominika
The Cookbook of Successful Short-Term Events. Organization and Continued Development of Outcomes Through an Iterative Process Technical Manual
2020.
Abstract | Links | BibTeX | Tags:
@manual{Holvitie2020,
title = {The Cookbook of Successful Short-Term Events. Organization and Continued Development of Outcomes Through an Iterative Process},
author = {Johannes Holvitie and Mikko Jaakola and Tuisku Polvinen and Niina K\"{a}yhk\"{o} and Carlos Gonzales Inca and Pawe\l Kisielewicz and Daniel Grzonka and Adrian Wid\lak and Piotr Szuster and Joanna Ko\lodziej and Dominika G\l\'{o}wczyk},
url = {https://www.grzonka.eu/wp-content/uploads/2025/07/Cookbook-BSA-ver-8-10-2020.pdf
https://balticsatapps.eu/cookbook-to-manage-special-characteristics-of-eo-data-within-hackathons-and-iterative-development-of-service-ideas/
https://balticsatapps.eu/promoting-innovation-in-earth-observation-based-services/cookbook-of-organising-eo-hackathons-and-iterative-development-of-service-ideas/},
year = {2020},
date = {2020-00-00},
urldate = {2020-00-00},
pages = {76},
publisher = {The BalticSatApps project},
abstract = {The cookbook focuses on the iterative development process wherein ideas and needs are systematically combined with skilled solution area experts and enthusiastic developers who are equipped with fitting tools and data. The outcomes of these combinations are analysed and it is identified if and how reapplying the previous (i.e. iterating) can bring the outcome closer to an effective and self-sustained innovation.
The ideas are converted into innovations by iterating aforedescribed expertise in various events. This publication discusses matters that need to be taken into account prior to the events, the types of events themselves, and issues that need to be considered afterwards. Sections refer to one another in order to highlight iterative dependencies and possibilities.},
keywords = {},
pubstate = {published},
tppubtype = {manual}
}
The cookbook focuses on the iterative development process wherein ideas and needs are systematically combined with skilled solution area experts and enthusiastic developers who are equipped with fitting tools and data. The outcomes of these combinations are analysed and it is identified if and how reapplying the previous (i.e. iterating) can bring the outcome closer to an effective and self-sustained innovation.
The ideas are converted into innovations by iterating aforedescribed expertise in various events. This publication discusses matters that need to be taken into account prior to the events, the types of events themselves, and issues that need to be considered afterwards. Sections refer to one another in order to highlight iterative dependencies and possibilities.
The ideas are converted into innovations by iterating aforedescribed expertise in various events. This publication discusses matters that need to be taken into account prior to the events, the types of events themselves, and issues that need to be considered afterwards. Sections refer to one another in order to highlight iterative dependencies and possibilities.
2019
Grzonka, Daniel; Kołodziej, Joanna; Jakóbik, Agnieszka
Agent–based monitoring of the task scheduling in computational clouds Journal Article
In: Journal of Intelligent & Fuzzy Systems, vol. 37, iss. 6, pp. 7481-7492, 2019, ISSN: 1064-1246.
Abstract | Links | BibTeX | Tags:
@article{bpk89740,
title = {Agent\textendashbased monitoring of the task scheduling in computational clouds},
author = {Daniel Grzonka and Joanna Ko\lodziej and Agnieszka Jak\'{o}bik},
url = {https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs179355},
doi = {10.3233/JIFS-179355},
issn = {1064-1246},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {Journal of Intelligent \& Fuzzy Systems},
volume = {37},
issue = {6},
pages = {7481-7492},
abstract = {The monitoring of the computational processes in highly distributed environments remains challenging in today’s High Performance Computing. In this paper, we define the agent-based cloud monitoring system for supporting the computational tasks scheduling and resource allocation. The system consists of two types of agents, which may decide about the initialization of the schedule execution and monitor the work of the cloud computational nodes. The decision about running the new scheduling process is based on the expected number of available computational units in the specified time window. The efficiency of the proposed MAS-based model was justified through 40 empirical tests, where clouds without and within the MAS support were compared. The multiagent system (MAS) effectiveness has been expressed in the average number of floating point operations completed at the cloud resources in one second. The obtained results show the importance of setting the optimal initial time for execution of the new schedule. Our experiments show that for running the new schedule, at least 25% of the computing units in the clouds should be in the idle mode. Also the batches of tasks should not be too large, cause the waiting time for new schedule for execution should be short and not greater than 10% of expected batch execution time.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The monitoring of the computational processes in highly distributed environments remains challenging in today’s High Performance Computing. In this paper, we define the agent-based cloud monitoring system for supporting the computational tasks scheduling and resource allocation. The system consists of two types of agents, which may decide about the initialization of the schedule execution and monitor the work of the cloud computational nodes. The decision about running the new scheduling process is based on the expected number of available computational units in the specified time window. The efficiency of the proposed MAS-based model was justified through 40 empirical tests, where clouds without and within the MAS support were compared. The multiagent system (MAS) effectiveness has been expressed in the average number of floating point operations completed at the cloud resources in one second. The obtained results show the importance of setting the optimal initial time for execution of the new schedule. Our experiments show that for running the new schedule, at least 25% of the computing units in the clouds should be in the idle mode. Also the batches of tasks should not be too large, cause the waiting time for new schedule for execution should be short and not greater than 10% of expected batch execution time.
Tchórzewski, Jacek; Jakóbik, Agnieszka; Grzonka, Daniel
Towards ANN-based scalable hashing algorithm for secure task processing in computational clouds Proceedings Article
In: Iacono, Mauro; Palmieri, Francesco; Gribaudo, Marco; Ficco, Massimo (Ed.): Proceedings of the 33rd International ECMS Conference on Modelling and Simulation : ECMS 2019, June 11th - June 14th, 2019, Caserta, Italy, pp. 421-427, European Council for Modelling and Simulation, [S.l.], 2019, ISSN: 2522-2422.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk88472,
title = {Towards ANN-based scalable hashing algorithm for secure task processing in computational clouds},
author = {Jacek Tch\'{o}rzewski and Agnieszka Jak\'{o}bik and Daniel Grzonka},
editor = {Mauro Iacono and Francesco Palmieri and Marco Gribaudo and Massimo Ficco},
url = {http://www.scs-europe.net/dlib/2019/ecms2019acceptedpapers/0421_dis_ecms2019_0050.pdf},
doi = {10.7148/2019-0421},
issn = {2522-2422},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {Proceedings of the 33rd International ECMS Conference on Modelling and Simulation : ECMS 2019, June 11th - June 14th, 2019, Caserta, Italy},
volume = {33},
number = {1},
pages = {421-427},
publisher = {European Council for Modelling and Simulation},
address = {[S.l.]},
series = {Communications of the ECMS},
abstract = {Task processing security is a key challenge in large scale distributed environments such as computational clouds. Methods that guarantee the identification and integrity of the data are hash functions. Their comput-ing load is high. Security models are expected to have an insignificant impact on the performance of the com-puting environment. In this paper, we have proposed the ANN-based model for scalable hashing of tasks re-sults. The model is named Dynamic ANN-based Light Hashing Function. In the presented approach the hash length may be changed. The length of the hash affects the number of cryptographic operations performed and influences time devoted to the task processing. There-fore, applying hash having longer output allows loading the fast computing resources more. Using shorter hash length enables to unload the slow computing units. Our approach allows selecting such parameters of crypto-graphic algorithms that will not significantly affect the makespan of a task batch.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Task processing security is a key challenge in large scale distributed environments such as computational clouds. Methods that guarantee the identification and integrity of the data are hash functions. Their comput-ing load is high. Security models are expected to have an insignificant impact on the performance of the com-puting environment. In this paper, we have proposed the ANN-based model for scalable hashing of tasks re-sults. The model is named Dynamic ANN-based Light Hashing Function. In the presented approach the hash length may be changed. The length of the hash affects the number of cryptographic operations performed and influences time devoted to the task processing. There-fore, applying hash having longer output allows loading the fast computing resources more. Using shorter hash length enables to unload the slow computing units. Our approach allows selecting such parameters of crypto-graphic algorithms that will not significantly affect the makespan of a task batch.
Kołodziej, Joanna; Grzonka, Daniel; Widłak, Adrian; Kisielewicz, Paweł
Ultra Wide Band Body Area Networks: Design and integration with computational clouds Book Chapter
In: Kołodziej, Joanna; González-Vélez, Horacio (Ed.): High-performance modelling and simulation for big data applications : selected results of the COST action IC1406 cHiPSet, vol. 11400, pp. 279-306, Springer, Cham, 2019, ISBN: 978-3-030-16272-6.
Abstract | Links | BibTeX | Tags:
@inbook{bpk86902,
title = {Ultra Wide Band Body Area Networks: Design and integration with computational clouds},
author = {Joanna Ko\lodziej and Daniel Grzonka and Adrian Wid\lak and Pawe\l Kisielewicz},
editor = {Joanna Ko\lodziej and Horacio Gonz\'{a}lez-V\'{e}lez},
url = {https://link.springer.com/chapter/10.1007/978-3-030-16272-6_10},
doi = {10.1007/978-3-030-16272-6_10},
isbn = {978-3-030-16272-6},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {High-performance modelling and simulation for big data applications : selected results of the COST action IC1406 cHiPSet},
volume = {11400},
pages = {279-306},
publisher = {Springer},
address = {Cham},
series = {Lecture Notes in Computer Science},
abstract = {Body Area Networks (BANs) connect together nodes attached to a human body and transfer the data to an external infrastructure. The wireless communication channel and a variety of miniature sensor devices have lead to many useful applications of BANs, such as healthcare monitoring, military and emergency coordination, rescue services, sports, and entertainment. The Ultra Wide Band (UWB) communication model is widely used in wireless body area networks. UWB Radio Frequency (RF) technology provides robust and energy efficient transmission of data and signals through wireless networks. This chapter surveys recent models, applications and research challenges for future generation UWB RF technology for BANs. The chapter also discusses the state-of-the art in the cloud-based support for data storage and analysis in mobile health monitoring. Security issues for BANs in general and mobile health monitoring are addressed as a key aspect of the recent developments in the domain.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Body Area Networks (BANs) connect together nodes attached to a human body and transfer the data to an external infrastructure. The wireless communication channel and a variety of miniature sensor devices have lead to many useful applications of BANs, such as healthcare monitoring, military and emergency coordination, rescue services, sports, and entertainment. The Ultra Wide Band (UWB) communication model is widely used in wireless body area networks. UWB Radio Frequency (RF) technology provides robust and energy efficient transmission of data and signals through wireless networks. This chapter surveys recent models, applications and research challenges for future generation UWB RF technology for BANs. The chapter also discusses the state-of-the art in the cloud-based support for data storage and analysis in mobile health monitoring. Security issues for BANs in general and mobile health monitoring are addressed as a key aspect of the recent developments in the domain.
Nejkovic, Valentina; Visa, Ari; Tosic, Milorad; Petrovic, Nenad; Valkama, Mikko; Koivisto, Mike; Talvitie, Jukka; Rancic, Svetozar; Grzonka, Daniel; Tchorzewski, Jacek; Kuonen, Pierre; Gortazar, Francisco
Big data in 5G distributed applications Book Chapter
In: Kołodziej, Joanna; González-Vélez, Horacio (Ed.): High-performance modelling and simulation for big data applications : selected results of the COST action IC1406 cHiPSet, vol. 11400, pp. 138-162, Springer, Cham, 2019, ISBN: 978-3-030-16272-6.
Abstract | Links | BibTeX | Tags:
@inbook{bpk86864,
title = {Big data in 5G distributed applications},
author = {Valentina Nejkovic and Ari Visa and Milorad Tosic and Nenad Petrovic and Mikko Valkama and Mike Koivisto and Jukka Talvitie and Svetozar Rancic and Daniel Grzonka and Jacek Tchorzewski and Pierre Kuonen and Francisco Gortazar},
editor = {Joanna Ko\lodziej and Horacio Gonz\'{a}lez-V\'{e}lez},
url = {https://link.springer.com/chapter/10.1007/978-3-030-16272-6_5},
doi = {10.1007/978-3-030-16272-6_5},
isbn = {978-3-030-16272-6},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {High-performance modelling and simulation for big data applications : selected results of the COST action IC1406 cHiPSet},
volume = {11400},
pages = {138-162},
publisher = {Springer},
address = {Cham},
series = {Lecture Notes in Computer Science},
abstract = {Fifth generation mobile networks (5G) will rather supplement than replace current 4G networks by dramatically improving their bandwidth, capacity and reliability. This way, much more demanding use cases that simply are not achievable with today’s networks will become reality - from home entertainment, to product manufacturing and healthcare. However, many of them rely on Internet of Things (IoT) devices equipped with low-cost transmitters and sensors that generate enormous amount of data about their environment. Therefore, due to large scale of 5G systems, combined with their inherent complexity and heterogeneity, Big Data and analysis techniques are considered as one of the main enablers of future mobile networks. In this work, we recognize 5G use cases from various application domains and list the basic requirements for their development and realization.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Fifth generation mobile networks (5G) will rather supplement than replace current 4G networks by dramatically improving their bandwidth, capacity and reliability. This way, much more demanding use cases that simply are not achievable with today’s networks will become reality - from home entertainment, to product manufacturing and healthcare. However, many of them rely on Internet of Things (IoT) devices equipped with low-cost transmitters and sensors that generate enormous amount of data about their environment. Therefore, due to large scale of 5G systems, combined with their inherent complexity and heterogeneity, Big Data and analysis techniques are considered as one of the main enablers of future mobile networks. In this work, we recognize 5G use cases from various application domains and list the basic requirements for their development and realization.
2018
Grzonka, Daniel
Polska Akademia Nauk. Instytut Podstawowych Problemów Techniki, 2018.
Abstract | Links | BibTeX | Tags:
@phdthesis{bpk86861,
title = {Inteligentne systemy monitoringu proces\'{o}w harmonogramowania w rozproszonych \'{s}rodowiskach du\.{z}ej skali w uj\k{e}ciu wieloagentowym : rozprawa doktorska},
author = {Daniel Grzonka},
url = {http://www.ippt.pan.pl/repository/doktoraty/open/2018grzonka_d_doktorat.pdf},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
pages = {VII, 175},
address = {Krak\'{o}w},
school = {Polska Akademia Nauk. Instytut Podstawowych Problem\'{o}w Techniki},
abstract = {Over the last few years modern distributed computing environments, such as clouds, become more and more important. The increase in the popularity of this type of environment brings many challenges, among them the effective usage of resources, guaranteeing the appropriate quality of services, or supervision over the operation of the entire environment. Task scheduling processes have a significant impact on the proper functioning of such environments. The main goal of this study is to develop models of intelligent systems that monitor the processes of independent tasks scheduling in distributed large-scale computing environments. The role of such systems is not only the supervision of the process, but also its support. The proposed system is built of five types of agents that support the process of task scheduling through direct interference with evolutionary scheduling algorithm, support in making decisions on starting schedule generation, monitoring the performance of tasks and correcting the expected times of task completion. Furthermore, as part of the thesis, a formal model for the dynamics of the distributed computing environment was developed, a new population representation for the evolutionary algorithm used in the scheduling process was proposed, the models of tasks and computing units were expanded, a notation was added to the description of monitoring systems of processes occurring in distributed environments and the pre-existing monitoring taxonomies were extended. The numerical experiments were carried out as part of a dedicated simulation environment. The obtained results prove that it is possible to improve the process of generating schedules of independent tasks through the agent-based intelligent monitoring system. Due to the proposed models, i.a. the scheduling generation process was accelerated, the time of executing whole task batch was reduced, as well as the average efficiency of the computing infrastructure and the reliability of prediction of task execution times were increased. The dissertation consist of the following chapters: Chapter 1 describes the themes of distributed systems and explains the motivation for the thesis. This chapter defines the goals of the work, as well as the research thesis. Chapter 2 introduces the main problem of the thesis - monitoring the task scheduling process, and presents the structure of the work. Chapter 3 presents the general problem of distributed computing environments monitoring with particular emphasis on cloud computing monitoring, the review and analysis of existing monitoring systems, the existing taxonomies of cloud monitoring systems, and the proposed extension of one of them. At the end of the chapter, a formal definition of the monitoring model was made. Chapter 4 is devoted to agent systems. The chapter describes the concept of the agent and its operating environment, it reviews the existing agent architectures, and describes the relationships between agents in multi-agent systems. Chapter 5 describes the problem of task scheduling. This chapter presents the existing classifications of scheduling problems. It also provides methods of how to solve this problems - a special emphasis was placed on independent batch scheduling. Then, the problem and scheduling criteria were defined and the so-called profiles of task models and calculation units were proposed. The last subchapter presents the idea of evolutionary approach for solving the problem of task scheduling. Chapter 6 presents original studies and models regarding the scheduling process and its monitoring. The chapter contains a description of the population representation for the problem of independent batch scheduling, a formal description of the distributed environment dynamics, a description of the schedule generation process, a multi-agent monitoring system, and a formal description of the proposed model. Chapter 7 presents the results of the conducted research, and shows the impact of the proposed models on the scheduling process and the quality of obtained schedules. Within the chapter, all proposed types of agents from the model were tested. Chapter 8 contains a summary of this work, including the most important conclusions and author\'s own contribution to the monitoring and supporting of task scheduling processes.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Over the last few years modern distributed computing environments, such as clouds, become more and more important. The increase in the popularity of this type of environment brings many challenges, among them the effective usage of resources, guaranteeing the appropriate quality of services, or supervision over the operation of the entire environment. Task scheduling processes have a significant impact on the proper functioning of such environments. The main goal of this study is to develop models of intelligent systems that monitor the processes of independent tasks scheduling in distributed large-scale computing environments. The role of such systems is not only the supervision of the process, but also its support. The proposed system is built of five types of agents that support the process of task scheduling through direct interference with evolutionary scheduling algorithm, support in making decisions on starting schedule generation, monitoring the performance of tasks and correcting the expected times of task completion. Furthermore, as part of the thesis, a formal model for the dynamics of the distributed computing environment was developed, a new population representation for the evolutionary algorithm used in the scheduling process was proposed, the models of tasks and computing units were expanded, a notation was added to the description of monitoring systems of processes occurring in distributed environments and the pre-existing monitoring taxonomies were extended. The numerical experiments were carried out as part of a dedicated simulation environment. The obtained results prove that it is possible to improve the process of generating schedules of independent tasks through the agent-based intelligent monitoring system. Due to the proposed models, i.a. the scheduling generation process was accelerated, the time of executing whole task batch was reduced, as well as the average efficiency of the computing infrastructure and the reliability of prediction of task execution times were increased. The dissertation consist of the following chapters: Chapter 1 describes the themes of distributed systems and explains the motivation for the thesis. This chapter defines the goals of the work, as well as the research thesis. Chapter 2 introduces the main problem of the thesis - monitoring the task scheduling process, and presents the structure of the work. Chapter 3 presents the general problem of distributed computing environments monitoring with particular emphasis on cloud computing monitoring, the review and analysis of existing monitoring systems, the existing taxonomies of cloud monitoring systems, and the proposed extension of one of them. At the end of the chapter, a formal definition of the monitoring model was made. Chapter 4 is devoted to agent systems. The chapter describes the concept of the agent and its operating environment, it reviews the existing agent architectures, and describes the relationships between agents in multi-agent systems. Chapter 5 describes the problem of task scheduling. This chapter presents the existing classifications of scheduling problems. It also provides methods of how to solve this problems - a special emphasis was placed on independent batch scheduling. Then, the problem and scheduling criteria were defined and the so-called profiles of task models and calculation units were proposed. The last subchapter presents the idea of evolutionary approach for solving the problem of task scheduling. Chapter 6 presents original studies and models regarding the scheduling process and its monitoring. The chapter contains a description of the population representation for the problem of independent batch scheduling, a formal description of the distributed environment dynamics, a description of the schedule generation process, a multi-agent monitoring system, and a formal description of the proposed model. Chapter 7 presents the results of the conducted research, and shows the impact of the proposed models on the scheduling process and the quality of obtained schedules. Within the chapter, all proposed types of agents from the model were tested. Chapter 8 contains a summary of this work, including the most important conclusions and author's own contribution to the monitoring and supporting of task scheduling processes.
Fernández-Cerero, Damián; Jakóbik, Agnieszka; Grzonka, Daniel; Kołodziej, Joanna; Fernández-Montes, Alejandro
Security supportive energy-aware scheduling and energy policies for cloud environments Journal Article
In: Journal of Parallel and Distributed Computing, vol. 119, pp. 191-202, 2018, ISSN: 0743-7315.
Abstract | Links | BibTeX | Tags:
@article{bpk82877,
title = {Security supportive energy-aware scheduling and energy policies for cloud environments},
author = {Dami\'{a}n Fern\'{a}ndez-Cerero and Agnieszka Jak\'{o}bik and Daniel Grzonka and Joanna Ko\lodziej and Alejandro Fern\'{a}ndez-Montes},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0743731518302843},
doi = {10.1016/j.jpdc.2018.04.015},
issn = {0743-7315},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
journal = {Journal of Parallel and Distributed Computing},
volume = {119},
pages = {191-202},
abstract = {Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of performance and energy-aware strategies for resource allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to combine energy and performance-aware scheduling policies in order to hibernate those virtual machines that operate in idle state. The efficiency achieved by applying the proposed models has been tested using a realistic large-scale CC system simulator. Obtained results show that a balance between low energy consumption and short makespan can be achieved. Several security constraints may be considered in this model. Each security constraint is characterized by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL are computed during the scheduling process in order to provide proper security services. Experimental results show that the proposed solution reduces up to 45% of the energy consumption of the CC system. Such significant improvement was achieved by the combination of an energy-aware scheduler with energy-efficiency policies focused on the hibernation of VMs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of performance and energy-aware strategies for resource allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to combine energy and performance-aware scheduling policies in order to hibernate those virtual machines that operate in idle state. The efficiency achieved by applying the proposed models has been tested using a realistic large-scale CC system simulator. Obtained results show that a balance between low energy consumption and short makespan can be achieved. Several security constraints may be considered in this model. Each security constraint is characterized by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL are computed during the scheduling process in order to provide proper security services. Experimental results show that the proposed solution reduces up to 45% of the energy consumption of the CC system. Such significant improvement was achieved by the combination of an energy-aware scheduler with energy-efficiency policies focused on the hibernation of VMs.
Grzonka, Daniel; Jakóbik, Agnieszka; Kołodziej, Joanna; Pllana, Sabri
Using a multi-agent system and artificial intelligence for monitoring and improving the cloud performance and security Journal Article
In: Future Generation Computer Systems, vol. 86, pp. 1106-1117, 2018, ISSN: 0167-739X.
Abstract | Links | BibTeX | Tags:
@article{bpk82872,
title = {Using a multi-agent system and artificial intelligence for monitoring and improving the cloud performance and security},
author = {Daniel Grzonka and Agnieszka Jak\'{o}bik and Joanna Ko\lodziej and Sabri Pllana},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0167739X17310531},
doi = {10.1016/j.future.2017.05.046},
issn = {0167-739X},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
journal = {Future Generation Computer Systems},
volume = {86},
pages = {1106-1117},
abstract = {Cloud Computing is one of the most intensively developed solutions for large-scale distributed processing. Effective use of such environments, management of their high complexity and ensuring appropriate levels of Quality of Service (QoS) require advanced monitoring systems. Such monitoring systems have to support the scalability, adaptability and reliability of Cloud. Most of existing monitoring systems do not incorporate any Artificial Intelligence (AI) algorithms for supporting the change inside the task stream or environment itself. They focus only on monitoring or enabling the control of the system as a part of a separated service. An effective monitoring system for the Cloud environment should gather information about all stages of tasks processing and should actively control the monitored environment. In this paper, we present a novel Multi-Agent System based Cloud Monitoring (MAS-CM) model that supports the performance and security of tasks gathering, scheduling and execution processes in large-scale service-oriented environments. Such models are explicitly designed to control the performance and security objectives of the environment. In our work, we focus on prevention of unauthorized task injection and modification, optimization of scheduling process and maximization of resource usage. We evaluate the effectiveness of MAS-CM empirically using an evolutionary driven implementation of Independent Batch Scheduler and FastFlow framework. The obtained results demonstrate the effectiveness of the proposed approach and the performance improvement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cloud Computing is one of the most intensively developed solutions for large-scale distributed processing. Effective use of such environments, management of their high complexity and ensuring appropriate levels of Quality of Service (QoS) require advanced monitoring systems. Such monitoring systems have to support the scalability, adaptability and reliability of Cloud. Most of existing monitoring systems do not incorporate any Artificial Intelligence (AI) algorithms for supporting the change inside the task stream or environment itself. They focus only on monitoring or enabling the control of the system as a part of a separated service. An effective monitoring system for the Cloud environment should gather information about all stages of tasks processing and should actively control the monitored environment. In this paper, we present a novel Multi-Agent System based Cloud Monitoring (MAS-CM) model that supports the performance and security of tasks gathering, scheduling and execution processes in large-scale service-oriented environments. Such models are explicitly designed to control the performance and security objectives of the environment. In our work, we focus on prevention of unauthorized task injection and modification, optimization of scheduling process and maximization of resource usage. We evaluate the effectiveness of MAS-CM empirically using an evolutionary driven implementation of Independent Batch Scheduler and FastFlow framework. The obtained results demonstrate the effectiveness of the proposed approach and the performance improvement.
2017
Jakóbik, Agnieszka; Grzonka, Daniel; Kołodziej, Joanna
Security supportive energy aware scheduling and scaling for cloud environments Proceedings Article
In: Paprika, Zita Zoltay; Horák, Péter; Váradi, Kata; Zwierczyk, Péter Tamás; Vidovics-Dancs, Ágnes; Rádics, János Péter (Ed.): 31st European Conference on Modelling and Simulation ECMS 2017, May 23rd - May 26th, 2017, Budapest, Hungary : proceedings, pp. 583-590, European Council for Modelling and Simulation, [S.l.], 2017, ISBN: 978-0-9932440-4-9.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk68350,
title = {Security supportive energy aware scheduling and scaling for cloud environments},
author = {Agnieszka Jak\'{o}bik and Daniel Grzonka and Joanna Ko\lodziej},
editor = {Zita Zoltay Paprika and Péter Horák and Kata Váradi and Péter Tamás Zwierczyk and Ágnes Vidovics-Dancs and János Péter Rádics},
url = {http://www.scs-europe.net/dlib/2017/ecms2017acceptedpapers/0583-dis_ECMS2017_0110.pdf},
doi = {10.7148/2017-0583},
isbn = {978-0-9932440-4-9},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {31st European Conference on Modelling and Simulation ECMS 2017, May 23rd - May 26th, 2017, Budapest, Hungary : proceedings},
pages = {583-590},
publisher = {European Council for Modelling and Simulation},
address = {[S.l.]},
series = {European Conference for Modelling and Simulation},
abstract = {Energy consumption is one of the most important problems in the era of Computational Clouds (CC). CC infrastructures must be elastic and scalable for being accessible by huge population of users in different geographical locations. It means also that CC energy utilization systems must be modern and dynamic in order to reduce the cost of using the cloud services and resources. In this paper, we develop the novel energy saving strategies for resource allocation and task scheduling in computational clouds. We present the new energy-aware scheduling policies and methods of scaling the virtual resources. The idea of the proposed models is based on Dynamic Voltage and Frequency Scaling (DVFS) techniques of modulation of the power of microprocessors. Additionally, the proposed model enables the monitoring of the energy consumption, which is necessary for providing the scheduling under the security criterion. The efficiency of the proposed models has been justified in the simple empirical analysis. The obtained results show the need to maintain a balance between energy consumption and task schedule execution.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Energy consumption is one of the most important problems in the era of Computational Clouds (CC). CC infrastructures must be elastic and scalable for being accessible by huge population of users in different geographical locations. It means also that CC energy utilization systems must be modern and dynamic in order to reduce the cost of using the cloud services and resources. In this paper, we develop the novel energy saving strategies for resource allocation and task scheduling in computational clouds. We present the new energy-aware scheduling policies and methods of scaling the virtual resources. The idea of the proposed models is based on Dynamic Voltage and Frequency Scaling (DVFS) techniques of modulation of the power of microprocessors. Additionally, the proposed model enables the monitoring of the energy consumption, which is necessary for providing the scheduling under the security criterion. The efficiency of the proposed models has been justified in the simple empirical analysis. The obtained results show the need to maintain a balance between energy consumption and task schedule execution.
Jakóbik, Agnieszka; Grzonka, Daniel; Palmieri, Francesco
Non-deterministic security driven meta scheduler for distributed cloud organizations Journal Article
In: Simulation Modelling Practice and Theory, vol. 76, pp. 67-81, 2017.
Abstract | Links | BibTeX | Tags:
@article{bpk67161,
title = {Non-deterministic security driven meta scheduler for distributed cloud organizations},
author = {Agnieszka Jak\'{o}bik and Daniel Grzonka and Francesco Palmieri},
url = {https://www.sciencedirect.com/science/article/abs/pii/S1569190X16302532},
doi = {10.1016/j.simpat.2016.10.011},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {Simulation Modelling Practice and Theory},
volume = {76},
pages = {67-81},
abstract = {Security is a very complex and challenging problem in Cloud organizations. Ensuring the security of operations within the cloud by also enforcing the users’ own security requirements, usually results in a complex tradeoff with the efficiency of the overall system. In this paper, we developed a novel architectural model enforcing cloud security, based on a multi-agent scheme and a security aware non-deterministic Meta Scheduler driven by genetic heuristics. Such model is explicitly designed to prevent Denial of Service and Timing Attacks over the cloud and has been demonstrated to be integrable within the well-known OpenStack platform. Additionally, we proposed two different models for assuring users security demands. The first is a scoring model that allows scheduling tasks only on the Virtual Machines offering proper security level. The second model takes into account the time spent on the necessary cryptographic operations dedicated to particular task. The above scheduling system has been simulated in order to assess the effectiveness of the proposed security architecture, resulting in an increased system safety and resiliency against attacks, without sensibly impacting the performance of the whole cloud environment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Security is a very complex and challenging problem in Cloud organizations. Ensuring the security of operations within the cloud by also enforcing the users’ own security requirements, usually results in a complex tradeoff with the efficiency of the overall system. In this paper, we developed a novel architectural model enforcing cloud security, based on a multi-agent scheme and a security aware non-deterministic Meta Scheduler driven by genetic heuristics. Such model is explicitly designed to prevent Denial of Service and Timing Attacks over the cloud and has been demonstrated to be integrable within the well-known OpenStack platform. Additionally, we proposed two different models for assuring users security demands. The first is a scoring model that allows scheduling tasks only on the Virtual Machines offering proper security level. The second model takes into account the time spent on the necessary cryptographic operations dedicated to particular task. The above scheduling system has been simulated in order to assess the effectiveness of the proposed security architecture, resulting in an increased system safety and resiliency against attacks, without sensibly impacting the performance of the whole cloud environment.
Jakóbik, Agnieszka; Grzonka, Daniel; Kołodziej, Joanna; Chis, Adriana E.; González-Vélez, Horacio
Energy efficient scheduling methods for computational grids and clouds Journal Article
In: Journal of Telecommunications and Information Technology : JTIT, no. 1, pp. 56-64, 2017, ISSN: 1509-4553.
Abstract | Links | BibTeX | Tags:
@article{bpk66355,
title = {Energy efficient scheduling methods for computational grids and clouds},
author = {Agnieszka Jak\'{o}bik and Daniel Grzonka and Joanna Ko\lodziej and Adriana E. Chis and Horacio Gonz\'{a}lez-V\'{e}lez},
url = {https://bibliotekanauki.pl/articles/309207.pdf},
issn = {1509-4553},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {Journal of Telecommunications and Information Technology : JTIT},
number = {1},
pages = {56-64},
abstract = {This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage profiles are presented together with energy efficiency measuring methods. Modelling of computing dynamics is discussed from the viewpoint of system identification theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage profiles are presented together with energy efficiency measuring methods. Modelling of computing dynamics is discussed from the viewpoint of system identification theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach.
2016
Jakóbik, Agnieszka; Grzonka, Daniel; Kołodziej, Joanna; González-Vélez, Horacio
Towards secure Non-Deterministic Meta-Scheduling for clouds Best Paper Proceedings Article
In: Claus, Thorsen; Herrmann, Frank; Manitz, Michael; Rose, Oliver (Ed.): ECMS 2016 : 30th European Conference on Modelling and Simulation, Regensburg, Germany, May 31st – June 3rd, 2016 : proceedings, pp. 596-602, ECMS - The European Council for Modelling and Simulation ECMS, Sbr.-Dudweiler, 2016, ISBN: 978-0-9932440-2-5.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk60363,
title = {Towards secure Non-Deterministic Meta-Scheduling for clouds},
author = {Agnieszka Jak\'{o}bik and Daniel Grzonka and Joanna Ko\lodziej and Horacio Gonz\'{a}lez-V\'{e}lez},
editor = { Thorsen Claus and Frank Herrmann and Michael Manitz and Oliver Rose},
url = {http://www.scs-europe.net/dlib/2016/ecms2016acceptedpapers/0596-dis_ECMS_0084.pdf},
doi = {10.7148/2016-0596},
isbn = {978-0-9932440-2-5},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {ECMS 2016 : 30th European Conference on Modelling and Simulation, Regensburg, Germany, May 31st \textendash June 3rd, 2016 : proceedings},
pages = {596-602},
publisher = {ECMS},
address = {Sbr.-Dudweiler},
organization = {ECMS - The European Council for Modelling and Simulation},
series = {European Conference for Modelling and Simulation},
abstract = {Task scheduling in large-scale distributed High Performance Computing (HPC) systems environments remains challenging research and engineering problem. There is a need of development of novel advanced scheduling techniques in order to optimise the resource utilisation. In this work, we develop the Agent Supported Non-Deterministic Meta Scheduler for cloud environments. This scheduling model is a simple combination of intelligent agent-based monitoring model for cloud system and security-aware cloud scheduler. In our model, scheduling, monitoring and reporting are provided in non-deterministic time intervals. An empirical case study using a FastFlow task farm was presented. It has demonstrates the effectiveness of the proposed solution.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Task scheduling in large-scale distributed High Performance Computing (HPC) systems environments remains challenging research and engineering problem. There is a need of development of novel advanced scheduling techniques in order to optimise the resource utilisation. In this work, we develop the Agent Supported Non-Deterministic Meta Scheduler for cloud environments. This scheduling model is a simple combination of intelligent agent-based monitoring model for cloud system and security-aware cloud scheduler. In our model, scheduling, monitoring and reporting are provided in non-deterministic time intervals. An empirical case study using a FastFlow task farm was presented. It has demonstrates the effectiveness of the proposed solution.
Grzonka, Daniel; Suchacka, Grażyna; Borowik, Barbara
Application of selected supervised classification methods to bank marketing campaign Journal Article
In: Information Systems in Management, vol. 5, no. 1, pp. 36-48, 2016, ISSN: 2084-5537.
Abstract | Links | BibTeX | Tags:
@article{bpk59441,
title = {Application of selected supervised classification methods to bank marketing campaign},
author = {Daniel Grzonka and Gra\.{z}yna Suchacka and Barbara Borowik},
url = {https://bibliotekanauki.pl/articles/94739.pdf},
issn = {2084-5537},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
journal = {Information Systems in Management},
volume = {5},
number = {1},
pages = {36-48},
abstract = {Supervised classification covers a number of data mining methods based on training data. These methods have been successfully applied to solve multi-criteria complex classification problems in many domains, including economical issues. In this paper we discuss features of some supervised classification methods based on decision trees and apply them to the direct marketing campaigns data of a Portuguese banking institution. We discuss and compare the following classification methods: decision trees, bagging, boosting, and random forests. A classification problem in our approach is defined in a scenario where a bank’s clients make decisions about the activation of their deposits. The obtained results are used for evaluating the effectiveness of the classification rules.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Supervised classification covers a number of data mining methods based on training data. These methods have been successfully applied to solve multi-criteria complex classification problems in many domains, including economical issues. In this paper we discuss features of some supervised classification methods based on decision trees and apply them to the direct marketing campaigns data of a Portuguese banking institution. We discuss and compare the following classification methods: decision trees, bagging, boosting, and random forests. A classification problem in our approach is defined in a scenario where a bank’s clients make decisions about the activation of their deposits. The obtained results are used for evaluating the effectiveness of the classification rules.
Grzonka, Daniel; Wilczyński, Andrzej; Kołodziej, Joanna
Data analytic and middleware: Multi-agent systems Technical Report
2016.
Abstract | Links | BibTeX | Tags:
@techreport{Grzonka2016,
title = {Data analytic and middleware: Multi-agent systems},
author = {Daniel Grzonka and Andrzej Wilczy\'{n}ski and Joanna Ko\lodziej},
url = {https://chipset-cost.eu/wp-content/uploads/2017/05/report-1.pdf#page=81},
year = {2016},
date = {2016-00-00},
urldate = {2016-00-00},
booktitle = {cHiPSet - Research Work Results},
issuetitle = {Grant Period 1},
abstract = {This document is the report of the research work of the cHiPSet members. It surveys the recent developments on infrastructures and middleware for Big Data modelling and simulation. The detailed taxonomy
of Big Data systems for life, physical, and socio-economical applications. is also presented.},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
This document is the report of the research work of the cHiPSet members. It surveys the recent developments on infrastructures and middleware for Big Data modelling and simulation. The detailed taxonomy
of Big Data systems for life, physical, and socio-economical applications. is also presented.
of Big Data systems for life, physical, and socio-economical applications. is also presented.
2015
Grzonka, Daniel
The analysis of OpenStack Cloud Computing Platform: features and performance Journal Article
In: Journal of Telecommunications and Information Technology : JTIT, no. 3, pp. 52-57, 2015, ISSN: 1509-4553.
Abstract | Links | BibTeX | Tags:
@article{bpk55097,
title = {The analysis of OpenStack Cloud Computing Platform: features and performance},
author = {Daniel Grzonka},
url = {https://www.grzonka.eu/?attachment_id=362},
issn = {1509-4553},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
journal = {Journal of Telecommunications and Information Technology : JTIT},
number = {3},
pages = {52-57},
abstract = {Over the decades the rapid development of broadly defined computer technologies, both software and hardware is observed. Unfortunately, software solutions are regularly behind in comparison to the hardware. On the other hand, the modern systems are characterized by a high demand for computing resources and the need for customization for the end users. As a result, the traditional way of system construction is too expensive, inflexible and it doesn’t have high resources utilization. Present article focuses on the problem of effective use of available physical and virtual resources based on the OpenStack Cloud Computing Platform. A number of conducted experiments allowed to evaluate computing resources utility and to analyse performance depending on the allocated resources. Additionally, the paper includes structural and functional analysis of the OpenStack Cloud Platform.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Over the decades the rapid development of broadly defined computer technologies, both software and hardware is observed. Unfortunately, software solutions are regularly behind in comparison to the hardware. On the other hand, the modern systems are characterized by a high demand for computing resources and the need for customization for the end users. As a result, the traditional way of system construction is too expensive, inflexible and it doesn’t have high resources utilization. Present article focuses on the problem of effective use of available physical and virtual resources based on the OpenStack Cloud Computing Platform. A number of conducted experiments allowed to evaluate computing resources utility and to analyse performance depending on the allocated resources. Additionally, the paper includes structural and functional analysis of the OpenStack Cloud Platform.
Grzonka, Daniel; Kołodziej, Joanna; Tao, Jie; Khan, Samme Ullah
Artificial Neural Network support to monitoring of the evolutionary driven security aware scheduling in computational distributed environments Journal Article
In: Future Generation Computer Systems, vol. 51, pp. 72-86, 2015, ISBN: 0167-739X.
Abstract | Links | BibTeX | Tags:
@article{bpk55051,
title = {Artificial Neural Network support to monitoring of the evolutionary driven security aware scheduling in computational distributed environments},
author = {Daniel Grzonka and Joanna Ko\lodziej and Jie Tao and Samme Ullah Khan},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0167739X14002258},
doi = {10.1016/j.future.2014.10.031},
isbn = {0167-739X},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
journal = {Future Generation Computer Systems},
volume = {51},
pages = {72-86},
abstract = {Monitoring of the system performance in highly distributed computing environments is a wide research area. In cloud and grid computing, it is usually restricted to the utilization and reliability of the resources. However, in today’s Computational Grids (CGs) and Clouds (CCs), the end users may define the special personal requirements and preferences in the resource and service selection, service functionality and data access. Such requirements may refer to the special individual security conditions for the protection of the data and application codes. Therefore, solving the scheduling problems in modern distributed environments remains still challenging for most of the well known schedulers, and the general functionality of the monitoring systems must be improved to make them efficient as schedulers supporting modules. In this paper, we define a novel model of security-driven grid schedulers supported by an Artificial Neural Network (ANN). ANN module monitors the schedule executions and learns about secure task\textendashmachine mappings from the observed machine failures. Then, the metaheuristic grid schedulers (in our case\textemdashgenetic-based schedulers) are supported by the ANN module through the integration of the sub-optimal schedules generated by the neural network, with the genetic populations of the schedules. The influence of the ANN support on the general schedulers’ performance is examined in the experiments conducted for four types of the grid networks (small, medium, large and very large grids), two security scheduling modes\textemdashrisky and secure scenarios, and six genetic-based grid schedulers. The generated empirical results show the high effectiveness of such monitoring support in reducing the values of the major scheduling criteria (makespan and flowtime), the run times of the schedulers and the grid resource failures.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Monitoring of the system performance in highly distributed computing environments is a wide research area. In cloud and grid computing, it is usually restricted to the utilization and reliability of the resources. However, in today’s Computational Grids (CGs) and Clouds (CCs), the end users may define the special personal requirements and preferences in the resource and service selection, service functionality and data access. Such requirements may refer to the special individual security conditions for the protection of the data and application codes. Therefore, solving the scheduling problems in modern distributed environments remains still challenging for most of the well known schedulers, and the general functionality of the monitoring systems must be improved to make them efficient as schedulers supporting modules. In this paper, we define a novel model of security-driven grid schedulers supported by an Artificial Neural Network (ANN). ANN module monitors the schedule executions and learns about secure task–machine mappings from the observed machine failures. Then, the metaheuristic grid schedulers (in our case—genetic-based schedulers) are supported by the ANN module through the integration of the sub-optimal schedules generated by the neural network, with the genetic populations of the schedules. The influence of the ANN support on the general schedulers’ performance is examined in the experiments conducted for four types of the grid networks (small, medium, large and very large grids), two security scheduling modes—risky and secure scenarios, and six genetic-based grid schedulers. The generated empirical results show the high effectiveness of such monitoring support in reducing the values of the major scheduling criteria (makespan and flowtime), the run times of the schedulers and the grid resource failures.
Grzonka, Daniel; Szczygieł, Michał; Bernasiewicz, Artur; Wilczyński, Andrzej; Liszka, Marek
Short analysis of implementation and resource utilization for the OpenStack cloud computing platform Proceedings Article
In: Mladenov, Valeri M.; Spasov, Grisha; Georgieva, Petia; Petrova, Galidiya (Ed.): ECMS 2015 : 29th European Conference on Modelling and Simulation, Albena (Varna), Bulgaria, May 26th - 29th, 2015 : proceedings, pp. 608-614, ECMS - The European Council for Modelling and Simulation ECMS, Sbr.-Dudweiler, 2015, ISBN: 978-0-9932440-0-1.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk54259,
title = {Short analysis of implementation and resource utilization for the OpenStack cloud computing platform},
author = {Daniel Grzonka and Micha\l Szczygie\l and Artur Bernasiewicz and Andrzej Wilczy\'{n}ski and Marek Liszka},
editor = {Valeri M. Mladenov and Grisha Spasov and Petia Georgieva and Galidiya Petrova},
url = {http://www.scs-europe.net/dlib/2015/ecms2015acceptedpapers/0608-dis_ECMS2015_0100.pdf},
doi = {10.7148/2015-0608},
isbn = {978-0-9932440-0-1},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
booktitle = {ECMS 2015 : 29th European Conference on Modelling and Simulation, Albena (Varna), Bulgaria, May 26th - 29th, 2015 : proceedings},
pages = {608-614},
publisher = {ECMS},
address = {Sbr.-Dudweiler},
organization = {ECMS - The European Council for Modelling and Simulation},
series = {European Conference for Modelling and Simulation},
abstract = {The problem of efficient use of computer resources is the actual challenge for many years. Huge progress in the hardware development has left behind the development of software techniques. One of the most popular solutions for this problem is the idea of virtualization, which a natural continuation is cloud computing. Cloud computing is an innovative concept, where the resources are virtualized, dynamically extended and provided as highly personalized services. In this paper, we present a short analysis of open-source cloud technology - OpenStack. We described OpenStack architecture, requirements, setup process, and related problems. We also conducted a thorough analysis of resource utility - both at full load and without. In our experiments we have analyzed the performance depending on the allocation of virtual resources. Through our work we pointed out aspects which deserve attention by choosing an OpenStack platform. Additionally, we draw attention to the burden on the use of technologies such as OpenStack cloud.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The problem of efficient use of computer resources is the actual challenge for many years. Huge progress in the hardware development has left behind the development of software techniques. One of the most popular solutions for this problem is the idea of virtualization, which a natural continuation is cloud computing. Cloud computing is an innovative concept, where the resources are virtualized, dynamically extended and provided as highly personalized services. In this paper, we present a short analysis of open-source cloud technology - OpenStack. We described OpenStack architecture, requirements, setup process, and related problems. We also conducted a thorough analysis of resource utility - both at full load and without. In our experiments we have analyzed the performance depending on the allocation of virtual resources. Through our work we pointed out aspects which deserve attention by choosing an OpenStack platform. Additionally, we draw attention to the burden on the use of technologies such as OpenStack cloud.
2014
Grzonka, Daniel; Kołodziej, Joanna; Tao, Jie
Using Artificial Neural Network for monitoring and supporting the grid scheduler performance Proceedings Article
In: Squazzoni, Flaminio; Baronio, Fabio; Archetti, Claudia; Castellani, Marco (Ed.): ECMS 2014 : 28th European Conference on Modelling and Simulation, May 27-30, 2014, Brescia, Italy : proceedings, pp. 515-522, ECMS - European Council for Modelling and Simulation ECMS, Dudweiler, 2014, ISBN: 978-0-9564944-8-1.
Abstract | Links | BibTeX | Tags:
@inproceedings{bpk53584,
title = {Using Artificial Neural Network for monitoring and supporting the grid scheduler performance},
author = {Daniel Grzonka and Joanna Ko\lodziej and Jie Tao},
editor = {Flaminio Squazzoni and Fabio Baronio and Claudia Archetti and Marco Castellani},
url = {http://www.scs-europe.net/dlib/2014/ecms14papers/dis_ECMS2014_0136.pdf},
doi = {10.7148/2014-0515},
isbn = {978-0-9564944-8-1},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
booktitle = {ECMS 2014 : 28th European Conference on Modelling and Simulation, May 27-30, 2014, Brescia, Italy : proceedings},
pages = {515-522},
publisher = {ECMS},
address = {Dudweiler},
organization = {ECMS - European Council for Modelling and Simulation},
series = {European Conference for Modelling and Simulation},
abstract = {Task scheduling and resource allocations are the key issues for computational grids. Distributed resources usually work at different autonomous domains with their own access and security policies that impact successful job executions across the domain boundaries. In this paper, we propose an Artificial Neural Network (ANN) approach for supporting the security awareness of evolutionary driven grid schedulers. Making a prior analysis of the trust levels of resources and security demand parameters of tasks, the neural network monitors the scheduling and task execution processes. In the result produce the tasks-machines mapping “suggestions”, which can be then utilized by the scheduler to reduce the makespan or increase the system throughput. In this paper, we report the development of risk-resilient genetic-based schedulers and their integration with an ANN module of the HyperSim-G Grid Simulator to evaluate the proposed model under the heterogeneity and large-scale system dynamics. The simulation results showed a significant impact of the ANN support on enhancing the effectiveness of the genetic-based meta-heuristics in reducing the cost of security awareness in grid scheduling.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Task scheduling and resource allocations are the key issues for computational grids. Distributed resources usually work at different autonomous domains with their own access and security policies that impact successful job executions across the domain boundaries. In this paper, we propose an Artificial Neural Network (ANN) approach for supporting the security awareness of evolutionary driven grid schedulers. Making a prior analysis of the trust levels of resources and security demand parameters of tasks, the neural network monitors the scheduling and task execution processes. In the result produce the tasks-machines mapping “suggestions”, which can be then utilized by the scheduler to reduce the makespan or increase the system throughput. In this paper, we report the development of risk-resilient genetic-based schedulers and their integration with an ANN module of the HyperSim-G Grid Simulator to evaluate the proposed model under the heterogeneity and large-scale system dynamics. The simulation results showed a significant impact of the ANN support on enhancing the effectiveness of the genetic-based meta-heuristics in reducing the cost of security awareness in grid scheduling.
2013
Grzonka, Daniel
Application of high-performance techniques for solving linear systems of algebraic equations Journal Article
In: Journal of Telecommunications and Information Technology : JTIT, no. 4, pp. 85-91, 2013, ISSN: 1509-4553.
Abstract | Links | BibTeX | Tags:
@article{bpk53543,
title = {Application of high-performance techniques for solving linear systems of algebraic equations},
author = {Daniel Grzonka},
url = {https://bibliotekanauki.pl/articles/307729.pdf},
issn = {1509-4553},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
journal = {Journal of Telecommunications and Information Technology : JTIT},
number = {4},
pages = {85-91},
abstract = {Solving many problems in mechanics, engineering, medicine and other fields (e.g., diffusion tensor magnetic resonance imaging or finite element modeling) requires the efficient solving of algebraic equations. In many cases, such systems are very complex, with a large number of linear equations that are symmetric positive-defined (SPD). This paper is focused on improving the computational efficiency of solvers dedicated to linear systems based on incomplete and noisy SPD matrices by using a preconditioning technique \textendash Incomplete Cholesky Factorization \textendash and a modern set of processor instructions \textendash Advanced Vector Extension. The application of these techniques allows for a significant reduction in computational time, the number of iterations of conventional algorithms, and an overall improvement in calculation speed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Solving many problems in mechanics, engineering, medicine and other fields (e.g., diffusion tensor magnetic resonance imaging or finite element modeling) requires the efficient solving of algebraic equations. In many cases, such systems are very complex, with a large number of linear equations that are symmetric positive-defined (SPD). This paper is focused on improving the computational efficiency of solvers dedicated to linear systems based on incomplete and noisy SPD matrices by using a preconditioning technique – Incomplete Cholesky Factorization – and a modern set of processor instructions – Advanced Vector Extension. The application of these techniques allows for a significant reduction in computational time, the number of iterations of conventional algorithms, and an overall improvement in calculation speed.