The Architecture of a Distributed System for Data Mining Based on Cases
DOI:
https://doi.org/10.24160/1993-6982-2023-4-155-161Keywords:
case-based approach, data mining, distributed intelligent systems, multi-agent systems, microservicesAbstract
The article addresses matters concerned with developing the architecture of a distributed data mining system using case-based reasoning. Currently, due to the development and availability of cloud technologies, one of the most promising areas in the field of artificial intelligence is the development of distributed intelligent systems (DIS). These systems are characterized by a distribution of computing and information resources, which results in more efficient performance of the system due to the possibility to simultaneously process a large amount of data. It is proposed to construct a DIS according to the principle of multi-agent systems (MAS) consisting of autonomous nodes (agents). The article presents the DIS architecture constructed on the basis of intelligent agents and consisting of blocks representing a set of microservices. Matters concerned with software implementation of the case-based block microservices are discussed in detail.
References
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11. Еремеев А.П., Варшавский П.Р., Поляков С.А. Программная реализация модуля анализа данных на основе прецедентов для распределенных интеллектуальных систем // Программные продукты и системы. 2021. Т. 34. № 3. С. 381—389.
12. Varshavskii P., Alekhin R., Polyakov S., Blashonkov T., Mukhacheva I. Development of a Modular Case-based Reasoning System for Data Analysis // Proc. Intern. Youth Conf. Radio Electronics, Electrical and Power Eng. 2020. Pp. 458—461.
13. Eremeev A., Varshavskii P., Kozhevnikov A., Polyakov S. Integrated Approach for Data Mining Based on Case-based Reasoning and Neural Networks // Proc. Fifth Intern. Sci. Conf. Intelligent Information Technologies for Industry. 2021. Pp. 15—23.
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Для цитирования: Варшавский П.Р., Поляков С.А. Архитектура распределенной системы для интеллектуального анализа данных на основе прецедентов // Вестник МЭИ. 2023. № 4. С. 155—161. DOI: 10.24160/ 1993-6982-2023-4-155-161
#
1. Ponomarev S. Voronkov A.E. Multi-agent Systems and Decentralized Artificial Superintelligence [Elektron. Resurs] https://arxiv.org/abs/1702.08529 (Data Obrashcheniya 26.12.2022)/
2. Balaji, P., Srinivasan D. An Introduction to Multi-agent Systems. Innovations in Multi-agent Systems and Applications. N.-Y.: Springer. 2010:1—27.
3. Andreadis G. e. a. Classification and Review of Multi-agents Systems in the Manufacturing Section. Proc. Eng. 2014;69:282—290.
4. Tarasov V.B. Ot Mnogoagentnykh Sistem k Intellektual'nym Organizatsiyam: Filosofiya, Psikhologiya, Informatika. M.: Editorial URSS, 2002. (in Russian).
5. FIPA: The Foundation for Intelligent Physical Agents. Abstract Architecture Specification [Ofits. Sayt] http://www.fipa.org (Data Obrashcheniya 26.12.2022).
6. Shashikant I., Rajeev M., Rajkumar B. 2020: Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems. Proc. IEEE Cloud Summit, Harrisburg, 2020:1—10.
7. Galiautdinov R. Microservice-oriented Architecture in Distributed Artificial Intelligence Systems and the Language of AI in Bio-neural Systems. Intern. J. Appl. Research in Bioinformatics. 2020;10(2):18—27.
8. Newman S. Building Microservices. Sebastopol: O'Reilly Media, Inc., 2021.
9. Apache Kafka [Ofits. Sayt] https://www.ibm.com/cloud/learn/apache-kafka (Data Obrashcheniya 26.12.2022).
10. Varshavskiy P.R., Eremeev A.P. Modelirovanie Rassuzhdeniy na Osnove Pretsedentov v Intellektual'nykh Sistemakh Podderzhki Prinyatiya Resheniy. Iskusstvennyy Intellekt i Prinyatie Resheniy. 2009;2:45—47. (in Russian).
11. Eremeev A.P., Varshavskiy P.R., Polyakov S.A. Programmnaya Realizatsiya Modulya Analiza Dannykh na Osnove Pretsedentov dlya Raspredelennykh Intellektual'nykh Sistem. Programmnye Produkty i Sistemy. 2021;34;3:381—389. (in Russian).
12. Varshavskii P., Alekhin R., Polyakov S., Blashonkov T., Mukhacheva I. Development of a Modular Case-based Reasoning System for Data Analysis. Proc. Intern. Youth Conf. Radio Electronics, Electrical and Power Eng. 2020:458—461.
13. Eremeev A., Varshavskii P., Kozhevnikov A., Polyakov S. Integrated Approach for Data Mining Based on Case-based Reasoning and Neural Networks. Proc. Fifth Intern. Sci. Conf. Intelligent Information Technologies for Industry. 2021:15—23
---
For citation: Varshavskii P.R., Polyakov S.A. The Architecture of a Distributed System for Data Mining Based on Cases. Bulletin of MPEI. 2023;4:155—161. (in Russian). DOI: 10.24160/1993-6982-2023-4-155-161
2. Balaji, P., Srinivasan D. An Introduction to Multi-agent Systems // Innovations in Multi-agent Systems and Applications. N.-Y.: Springer. 2010. Pp. 1—27.
3. Andreadis G. e. a. Classification and Review of Multi-agents Systems in the Manufacturing Section // Proc. Eng. 2014. V. 69. Pp. 282—290.
4. Тарасов В.Б. От многоагентных систем к интеллектуальным организациям: философия, психология, информатика. М.: Эдиториал УРСС, 2002.
5. FIPA: The Foundation for Intelligent Physical Agents. Abstract Architecture Specification [Офиц. сайт] http://www.fipa.org (дата обращения 26.12.2022).
6. Shashikant I., Rajeev M., Rajkumar B. 2020: Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems // Proc. IEEE Cloud Summit, Harrisburg, 2020. Pp. 1—10.
7. Galiautdinov R. Microservice-oriented Architecture in Distributed Artificial Intelligence Systems and the Language of AI in Bio-neural Systems // Intern. J. Appl. Research in Bioinformatics. 2020. V. 10(2). Pp. 18—27.
8. Newman S. Building Microservices. Sebastopol: O'Reilly Media, Inc., 2021.
9. Apache Kafka [Офиц. сайт] https://www.ibm.com/cloud/learn/apache-kafka (дата обращения 26.12.2022).
10. Варшавский П.Р., Еремеев А.П. Моделирование рассуждений на основе прецедентов в интеллектуальных системах поддержки принятия решений // Искусственный интеллект и принятие решений. 2009. № 2. С. 45—47.
11. Еремеев А.П., Варшавский П.Р., Поляков С.А. Программная реализация модуля анализа данных на основе прецедентов для распределенных интеллектуальных систем // Программные продукты и системы. 2021. Т. 34. № 3. С. 381—389.
12. Varshavskii P., Alekhin R., Polyakov S., Blashonkov T., Mukhacheva I. Development of a Modular Case-based Reasoning System for Data Analysis // Proc. Intern. Youth Conf. Radio Electronics, Electrical and Power Eng. 2020. Pp. 458—461.
13. Eremeev A., Varshavskii P., Kozhevnikov A., Polyakov S. Integrated Approach for Data Mining Based on Case-based Reasoning and Neural Networks // Proc. Fifth Intern. Sci. Conf. Intelligent Information Technologies for Industry. 2021. Pp. 15—23.
---
Для цитирования: Варшавский П.Р., Поляков С.А. Архитектура распределенной системы для интеллектуального анализа данных на основе прецедентов // Вестник МЭИ. 2023. № 4. С. 155—161. DOI: 10.24160/ 1993-6982-2023-4-155-161
#
1. Ponomarev S. Voronkov A.E. Multi-agent Systems and Decentralized Artificial Superintelligence [Elektron. Resurs] https://arxiv.org/abs/1702.08529 (Data Obrashcheniya 26.12.2022)/
2. Balaji, P., Srinivasan D. An Introduction to Multi-agent Systems. Innovations in Multi-agent Systems and Applications. N.-Y.: Springer. 2010:1—27.
3. Andreadis G. e. a. Classification and Review of Multi-agents Systems in the Manufacturing Section. Proc. Eng. 2014;69:282—290.
4. Tarasov V.B. Ot Mnogoagentnykh Sistem k Intellektual'nym Organizatsiyam: Filosofiya, Psikhologiya, Informatika. M.: Editorial URSS, 2002. (in Russian).
5. FIPA: The Foundation for Intelligent Physical Agents. Abstract Architecture Specification [Ofits. Sayt] http://www.fipa.org (Data Obrashcheniya 26.12.2022).
6. Shashikant I., Rajeev M., Rajkumar B. 2020: Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems. Proc. IEEE Cloud Summit, Harrisburg, 2020:1—10.
7. Galiautdinov R. Microservice-oriented Architecture in Distributed Artificial Intelligence Systems and the Language of AI in Bio-neural Systems. Intern. J. Appl. Research in Bioinformatics. 2020;10(2):18—27.
8. Newman S. Building Microservices. Sebastopol: O'Reilly Media, Inc., 2021.
9. Apache Kafka [Ofits. Sayt] https://www.ibm.com/cloud/learn/apache-kafka (Data Obrashcheniya 26.12.2022).
10. Varshavskiy P.R., Eremeev A.P. Modelirovanie Rassuzhdeniy na Osnove Pretsedentov v Intellektual'nykh Sistemakh Podderzhki Prinyatiya Resheniy. Iskusstvennyy Intellekt i Prinyatie Resheniy. 2009;2:45—47. (in Russian).
11. Eremeev A.P., Varshavskiy P.R., Polyakov S.A. Programmnaya Realizatsiya Modulya Analiza Dannykh na Osnove Pretsedentov dlya Raspredelennykh Intellektual'nykh Sistem. Programmnye Produkty i Sistemy. 2021;34;3:381—389. (in Russian).
12. Varshavskii P., Alekhin R., Polyakov S., Blashonkov T., Mukhacheva I. Development of a Modular Case-based Reasoning System for Data Analysis. Proc. Intern. Youth Conf. Radio Electronics, Electrical and Power Eng. 2020:458—461.
13. Eremeev A., Varshavskii P., Kozhevnikov A., Polyakov S. Integrated Approach for Data Mining Based on Case-based Reasoning and Neural Networks. Proc. Fifth Intern. Sci. Conf. Intelligent Information Technologies for Industry. 2021:15—23
---
For citation: Varshavskii P.R., Polyakov S.A. The Architecture of a Distributed System for Data Mining Based on Cases. Bulletin of MPEI. 2023;4:155—161. (in Russian). DOI: 10.24160/1993-6982-2023-4-155-161
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Published
2023-04-12
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Section
Mathematical and Software Support of Computer Systems, Complexes and Computer Networks (Technical Sciences) (2.3.5)
