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Multi-Agent Systems for Adaptive and Efficient Job Scheduling Service in Grids

by Pooja Sapra, Minakshi Memoria, Sunaina
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 9
Year of Publication: 2010
Authors: Pooja Sapra, Minakshi Memoria, Sunaina
10.5120/206-346

Pooja Sapra, Minakshi Memoria, Sunaina . Multi-Agent Systems for Adaptive and Efficient Job Scheduling Service in Grids. International Journal of Computer Applications. 1, 9 ( February 2010), 26-30. DOI=10.5120/206-346

@article{ 10.5120/206-346,
author = { Pooja Sapra, Minakshi Memoria, Sunaina },
title = { Multi-Agent Systems for Adaptive and Efficient Job Scheduling Service in Grids },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 9 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number9/206-346/ },
doi = { 10.5120/206-346 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:45:26.532856+05:30
%A Pooja Sapra
%A Minakshi Memoria
%A Sunaina
%T Multi-Agent Systems for Adaptive and Efficient Job Scheduling Service in Grids
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 9
%P 26-30
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we propose an adaptive efficient job scheduling service model on Grids using multi agent systems and a market like Service level Agreement (SLA) negotiation protocol based on the Contract Net model. This job scheduling service model involves four types of agents: service user agents, service provider agents, local scheduler agents and inter-grid agents. Service provider agents provide services to service user agents by allocating resources using local scheduler agents. Service provider agents provide services to service user agents by allocating resources using local scheduler agents. The service provider agents may contact the inter-grid agents if enough resources are not available in their own grid. Inter-grid agents provide resources from the neighboring grid. The service provider agent may adapt the dedicated service according to its interactions with service user agent.

References
  1. Choi, H. R., Kim, H. S., Park, B. J., Park, Y. J., Whinston, A.B.: An agent for selecting optimal order set in EC marketplace. Decision Support Systems, 53(2003) 39-58.
  2. Czajkowski, K., Dan, A., Rofrano, J., Tuecke, S., Xu, M.: Agreement-based Service Management (WS-Agreement). Draft Global Grid Forum Recommendation Document (2003).
  3. Keller, A., Kar, G., Ludwig, H., Dan, A., Hellerstein, J.L.: Managing Dynamic Services: A Contract Based Approach to a Conceptual Architecture. Proceedings of the 8th IEEE/IFIP Network Operations and Management Symposium (2002) 513–528.
  4. Ouelhadj, D., Hanachi, C., Bouzouia, B.: Multi-agent architecture for distributed monitoring in flexible manufacturing systems (FMS). Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, USA (2000) 1120-1126.
  5. Ouelhadj, D., Cowling, P., Petrovic, S.: Contract net protocol for cooperative optimisation and dynamic scheduling of steel production. In: Ajith, Ibraham, Katrin, Franke and Mario, Koppen, (eds.): Intelligent Systems Design and Applications, Springer-Verlag (2003) 457-470.
  6. Smith, R.: The contract net protocol: high level communication and control in distributed problem solver. IEEE Transactions on Computers, 29 (1980) 1104-1113.
  7. O’Hare, G., Jennings, N. (Eds.): Foundations of Distributed Artificial Intelligence, Wiley, New York (1996).
  8. Shen, W., Norrie, D., Barthes, J. (eds.): Multi-agent systems for concurrent intelligent design and manufacturing, Taylor & Francis, London (2001).
  9. Abramson, D., Buyya, R., Giddy, J.: A computational economy for Grid computing and its implementation in the Nimrod-G resource broker. Future generation Computer Systems, 18 (2002) 1061-1074.
  10. Cao, J., Kerbyson, D., Nudd, G.: Performance evaluation of an agent-based resource management infrastructure for Grid computing. Proceedings of the First IEEE/ACM International Symposium on Cluster Computing and the Grid (2001) 311-318.
  11. Cao, J., Jarvis, S.: ARMS: An agent-based resource management system for Grid computing. Scientific Programming, 10(2002) 135-148.
  12. Rana, O. and Walker, D.: The Agent Grid: Agent-based resource integration in PSEs. Proceedings of the 16th IMACS World Congress on Scientific Computing, Applied Mathematics and Simulation, Lausanne, Switzerland (2000).
  13. Buyya, R., Abramson, D., Giddy, J., Stocking, H.: Economic models for resource management and scheduling in Grid computing. Concurrency and Computation: Practice and Experience, 14 (2002) 1507-1542.
  14. Wooldridge, M. (eds.): An introduction to multi-agent systems. John Wiley & Sons, Ltd., Chichester, England (2002).
  15. “A Multi-agent Infrastructure and a Service Level agreementNegotiation Protocol for Robust Scheduling in Grid Computing” by 1 D. Ouelhadj, 2J. Garibaldi, 3J. MacLaren, 4R. Sakellariou, 5K. Krishnakumar, 6Amnon Meisels
Index Terms

Computer Science
Information Sciences

Keywords

Scheduling SLA Multi-Agent Grid Computing

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