RESOURCE DISCOVERY IN DISTRIBUTED EXASCALE SYSTEMS USING A MULTI-AGENT MODEL: CATEGORIZATION OF AGENTS BASED ON THEIR CHARACTERISTICS
DOI:
https://doi.org/10.32010/26166127.2023.6.1.113.120Keywords:
HPC, Resource Discovery, Agents, Dynamic and Interactive Event, Exascale SystemsAbstract
Resource discovery is a crucial component in high-performance computing (HPC) systems. This paper presents a multi-agent model for resource discovery in distributed exascale systems. Agents are categorized based on resource types and behavior-specific characteristics. The model enables efficient identification and acquisition of memory, process, file, and IO resources. Through a comprehensive exploration, we highlight the potential of our approach in addressing resource discovery challenges in exascale computing systems, paving the way for optimized resource utilization and enhanced system performance.
Downloads
References
Adibi, E., & Khaneghah, E. M. (2018). Challenges of resource discovery to support distributed exascale computing environment. Azerbaijan Journal of High Performance Computing, 1(2), 168-178.
Adibi, E., & Mousavi Khaneghah, E. (2020). ExaRD: introducing a framework for empowerment of resource discovery to support distributed exascale computing systems with high consistency. Cluster Computing, 23, 3349-3369.
Castano, S., Ferrara, A., Montanelli, S., & Racca, G. (2004, April). Matching techniques for resource discovery in distributed systems using heterogeneous ontology descriptions. In International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004. (Vol. 1, pp. 360-366). IEEE.
Dimakopoulos, V. V., & Pitoura, E. (2003, August). A peer-to-peer approach to resource discovery in multi-agent systems. In International Workshop on Cooperative Information Agents (pp. 62-77). Berlin, Heidelberg: Springer Berlin Heidelberg.
Ding, S., Yuan, J., & Hu, L. (2005, March). A heuristic algorithm for agent-based grid resource discovery. In 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (pp. 222-225). IEEE.
Kambayashi, Y., & Harada, Y. (2007). A resource discovery method based on multi-agents in P2P systems. In Agent and Multi-Agent Systems: Technologies and Applications: First KES International Symposium, KES-AMSTA 2007, Wroclaw, Poland, May 31–June 1, 2007. Proceedings 1 (pp. 364-374). Springer Berlin Heidelberg.
Khaneghah, E. M., Aliev, A. R., Bakhishoff, U., & Adibi, E. (2018). The influence of exascale on resource discovery and defining an indicator. Azerbaijan Journal of High Performance Computing, 1(1), 3-19.
Raj, P., & Sekhar, C. (2020). Comparative Study on CPU GPU and TPU. Int. Journal of Computer Science and Information Technology for Education, 5, 31-38.
Selvaraj, C., & Anand, S. (2012). A survey on security issues of reputation management systems for peer-to-peer networks. Computer science review, 6(4), 145-160.
Tan, Y., & Zheng, Z. (2009, May). A multi-agent based resource discovery scheme for p2p systems. In 2009 International Workshop on Intelligent Systems and Applications (pp. 1-4). IEEE.
Tan, Y., Han, J., & Wu, Y. (2010). A multi-agent based efficient resource discovery mechanism for grid systems. Journal of Computational Information Systems, 6(11), 3623-3631.
Yamasaki, J., & Kambayashi, Y. (2010, November). Design an Implementation of Bee Hive in a Mult-agent Based Resource Discovery Method in P2P Systems. In 2010 First International Conference on Networking and Computing (pp. 292-293). IEEE.
Zarrin, J., Aguiar, R. L., & Barraca, J. P. (2018). Resource discovery for distributed computing systems: A comprehensive survey. Journal of parallel and distributed computing, 113, 127-166.
