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A multiagent brokering protocol for supporting Grid resource discovery

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Abstract

Resource discovery provides a mean to identify the set of resources that are capable of satisfying the job requirements. Scalability and adaptability are two key challenges of resource discovery in a Grid environment. To deal with both issues, the agent concept has been adopted to cope with unexpected events such as the failure of provider agents. Multiple broker agents are used to deal with huge amounts of data from multiple sources. In our multiagent protocol, three types of agents (user agent, provider agent, and broker agent) are used. Each broker agent connects user agents to provider agents using the connection algorithm which mainly consists of 4 stages: selection, evaluation, filtering, and recommendation. In the recommendation stage, two kinds of recommendation approaches (circular approach and multicast approach) are used for making recommendations to the user agents that failed to be matched to provider agents. Empirical results show that our approach using multiagent brokering protocol with the adaptable feature of coordinating load balance (the results of balanced case) has significantly good performance in terms of scalability and adaptability.

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References

  1. Cao J, Kerbyson DJ, Nudd GR (2001) Performance evaluation of an agent-based resource management infrastructure for Grid computing. In: Proceedings of the 1st international symposium on cluster computing and the Grid, May 15–18, p 311

    Google Scholar 

  2. Chunlin L, Layuan L (2003) Apply agent to build grid service management. J Netw Comput Appl 26:323–340

    Article  Google Scholar 

  3. Czajkowski K, Fitzgerald S, Foster I, Kesselman C (2001) Grid information services for distributed resource sharing. In: Proceedings of the 10th IEEE international symposium on high-performance distributed computing (HPDC-10)

    Google Scholar 

  4. Ding S, Yuan J, Ju J, Hu L (2005) A heuristic algorithm for agent-based Grid resource discovery. In: IEEE international conference on e-technology, e-commerce and e-service (EEE’05), pp 222–225

    Chapter  Google Scholar 

  5. Dominiak M, Ganzha M, Paprzycki M (2007) Selecting grid-agent-team to execute user-job-initial solution. In: Proceedings of the conference on complex intelligent and software intensive systems. IEEE CS Press, Los Alamitos, pp 249–256

    Google Scholar 

  6. Fitzgerald S, Foster I, Kesselman C, Laszewski GV, Smith W, Tuecke S (1997) A directory service for configuring high-performance distributed computations. In: Proceedings of the 6th IEEE symposium on high-performance distributed computing, pp 365–375

    Google Scholar 

  7. Fukuda M, Smith D, (2006) UWAgents: a mobile agent system optimized for grid computing. In: Proceedings of the 2006 international conference on Grid computing and applications (CGA 06), Las Vegas, NV, pp 107–113. CSREA

    Google Scholar 

  8. Kang J, Sim KM (2009) A brokering protocol for agent-based Grid resource discovery. Commun Comput Inf Sci 63:33–40 (Grid and Distributed Computing)

    Article  Google Scholar 

  9. Khanli LM, Kargar S (2010) FRDT: footprint resource discovery tree for grids. Future Gener Comput Syst 27:148–156

    Article  Google Scholar 

  10. Li F, Qi D, Zhang L, Zhang X, Zhang Z (2006) Research on novel dynamic resource management and job scheduling in Grid computing. In: Proceedings of IMSCCS, vol 1, pp 709–713

    Google Scholar 

  11. Naseer A, Stergioulas LK (2006) Resource discovery in Grids and other distributed environments: states of the art. Multiagent Grid Syst. 2(2):163–182

    MATH  Google Scholar 

  12. Sim KM, Chan R (2000) A brokering protocol for agent-based e-commerce. IEEE Trans Syst Man Cybern, Part C, Appl Rev 30(4):474–484

    Article  Google Scholar 

  13. Sim KM (2006) Guest editorial: Agent-based Grid computing. Appl Intell 25(2):127–129

    Article  Google Scholar 

  14. Ardaiz O, Artigas P, Eymann T, Freitag F, Navarro L, Reinicke M (2006) The Catallaxy approach for decentralized economic-based allocation in Grid resource and service markets. Appl Intell 25(2):131–145

    Article  Google Scholar 

  15. Li C, Li L (2006) Multi economic agent interaction for optimizing the aggregate utility of Grid users in computational grid. Appl Intell 25(2):147–158

    Article  MATH  Google Scholar 

  16. Dragoni N, Gaspari M, Guidi D (2006) An infrastructure to support cooperation of knowledge-level agents on the semantic Grid. Appl Intell 25(2):159–180

    Article  MATH  Google Scholar 

  17. Fukuda M, Kashiwagi K, Kobayashi S (2006) AgentTeamwork: coordinating Grid-computing jobs with mobile agents. Appl Intell 25(2):181–198

    Article  MATH  Google Scholar 

  18. Choi S, Baik M, Gil J, Jung S, Hwang C (2006) Adaptive group scheduling mechanism using mobile agents in peer-to-peer Grid computing environment. Appl Intell 25(2):199–221

    Article  MATH  Google Scholar 

  19. Naumenko A, Nikitin S, Terziyan V (2006) Service matching in agent systems. Appl Intell 25(2):223–237

    Article  MATH  Google Scholar 

  20. Sharma R, Soni VK, Mishra MK, Bhuyan P, Dey UC (2010) An agent based dynamic resource scheduling model with FCFS-job grouping strategy Grid computing. In: International conference on cluster and Grid computing systems (ICCGCS-2010), Italy, Rome

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MEST) (KRF-2009-220-D00092) . The authors would like to thank the Editor-in-Chief and the anonymous referees for their comments and suggestions.

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Correspondence to Kwang Mong Sim.

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Kang, J., Sim, K.M. A multiagent brokering protocol for supporting Grid resource discovery. Appl Intell 37, 527–542 (2012). https://doi.org/10.1007/s10489-012-0347-y

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