doi: 10.17586/2226-1494-2019-19-6-1086-1093


IMPLEMENTATION OF AGENT INTERACTION PROTOCOL WITHIN CLOUD INFRASTRUCTURE IN GEOGRAPHICALLY DISTRIBUTED DATA CENTERS

N. Y. Samokhin, A. A. Oreshkin, A. S. Suprun


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Samokhin N.Yu., Oreshkin A.A., Suprun A.S. Implementation of agent interaction protocol within cloud infrastructure in geographically distributed data centers. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 6, pp. 1086–1093 (in Russian). doi: 10.17586/2226-1494-2019-19-6-1086-1093


Abstract
A cloud system for geographically distributed data centers is presented. An approach is based on the principle of multi-agent structure (microservices). A special interaction protocol was developed for agents’ communication operating in asynchronous mode. The asynchronous behavior of the agent interaction system is achieved through the use of a specially developed algorithm. The program that implements the proposed algorithm is written in the Python programming language. This solution uses relational databases and queuing systems. A relational database stores requests and responses from the agents. A message broker is necessary for exchanging YAML messages with identifiers of these requests and responses. The developed software was tested a prototype of a scalable geographically distributed data center. An original technical solution was obtained that successfully passed a series of tests and was implemented within existing cloud infrastructure. Features of applying the RabbitMQ queuing system and PostgreSQL database management system in cluster mode with traffic encryption are indicated. The use of the developed model appears to be promising oriented for highly loaded distributed systems.

Keywords: cloud, distributed, data center, message broker, RabbitMQ, PostgreSQL

Acknowledgements. The research was carried out with the financial support of the Ministry of Education and Science of the Russian Federation (Contract No. 03.G25.31.0229).

References
  1. Khoruzhnikov S.E., Shevel A.Ye. Management system for scalable geographically distributed data center. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 5, pp. 931–938. (in Russian). doi: 10.17586/2226-1494-2019-19-5-931-938
  2. De Benedictis A., Rak M., Turtur M., Villano U. REST-Based SLA management for cloud applications. Proc. IEEE 24th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE 2015), 2015, pp. 93–98. doi: 10.1109/WETICE.2015.36
  3. Benchara F.Z., Youssfi M., Bouattane O., Ouajji H. A new efficient distributed computing middleware based on cloud micro-services for HPC. Proc. 5th International Conference on Multimedia Computing and Systems (ICMCS), 2016, pp. 354–359. doi: 10.1109/ICMCS.2016.7905644
  4. Esposito C., Palmieri F., Choo K.-K. R. Cloud message queueing and notification: challenges and opportunities. IEEE Cloud Computing, 2018, vol. 5, no 2, pp. 11–16. doi: 10.1109/MCC.2018.022171662
  5. Salah K., Sheltami T.R. Performance modeling of cloud apps using message queueing as a service (MaaS). Proc. 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), 2017, pp. 65–71. doi: 10.1109/ICIN.2017.7899251
  6. Ionescu V.M. The analysis of the performance of RabbitMQ and ActiveMQ. Proc. 14th RoEduNet International Conference - Networking in Education and Research (RoEduNet NER), 2015, pp. 132–137. doi: 10.1109/RoEduNet.2015.7311982
  7. Hong X.J., Sik Yang H., Kim Y.H. Performance analysis of RESTful API and RabbitMQ for microservice web application. Proc. 9th International Conference on Information and Communication Technology Convergence (ICTC), 2018, pp. 257–259. doi: 10.1109/ICTC.2018.8539409
  8. Wang J., Bai X., Li L., Ji Z., Ma H. A Model-based framework for cloud API testing. Proc.  41st IEEE Annual Computer Software and Applications Conference (COMPSAC), 2017, pp. 60–65. doi: 10.1109/COMPSAC.2017.24
  9. Momjian B. PostgreSQL: Introduction and concepts. AddisonWesley, 2002, 490 p.
  10. Chen Y., Paxson V., Katz R. What’s new about cloud computing security?. Technical Report UCB/EECS-2010-5. Berkeley, 2010.
  11. Ali-Eldin A.H. Capacity Scaling for Elastic Compute Clouds. Dissertation. Umea University, Sweden, 2013, 90 p.
  12. Vinoski S. Advanced message queuing protocol. IEEE Internet Computing, 2006, vol. 10, no. 6, pp. 87–89. doi: 10.1109/MIC.2006.116
  13. Rostanski M., Grochla K., Seman A. Evaluation of highly available and fault-tolerant middleware clustered architectures using RabbitMQ. Proc. Federated Conference on Computer Science and Information Systems, 2014, vol. 2, pp. 879–884. doi: 10.15439/2014F48
  14. Budrean S., Li Y., Desai B.C. High availability solutions for transactional database systems. Proc. 7th International Database Engineering and Applications Symposium (IDEAS), 2003, pp. 347–355. doi: 10.1109/IDEAS.2003.1214952
  15. Afanasev M.Ya., Fedosov Yu.V., Krylova A.A., Shorokhov S.A.. Performance evaluation of the message queue protocols to transfer binary JSON in a distributed CNC system. Proc. 15th IEEE International Conference on Industrial Informatics (INDIN), 2017, pp. 357–362. doi: 10.1109/INDIN.2017.8104798
  16. Samokhin N.Yu., Khoruzhnikov S.E., Trubnikova V.M., Akhmedzyanova R.R., Bulykina A.B. Information on utilization of data center resources with message broker implementation. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2018, vol. 18, no. 5, pp. 858–862. doi: 10.17586/2226-1494-2018-18-5-858-862
  17. Fedchenkov P.V., Khoruzhnikov S.E., Samokhin N.Y., Shevel A.Y. The designing of cloud infrastructure consisting of geographically distributed data centers. CEUR Workshop Proceedings, 2018, vol. 2267, pp. 32–36.


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