Abstract
A Grid information system should rely upon two basic features: the replication and dissemination of information about Grid resources, and an intelligent logical distribution of such information among Grid hosts. This paper examines an approach based on multi agent systems to build an information systems in which metadata related to Grid resources is disseminated and logically organized according to a semantic classification of resources. Agents collect resources belonging to the same class in a restricted region of the Grid, so decreasing the system entropy. A semi-informed resource discovery protocol exploits the agents’ work: query messages issued by clients are driven towards “representative peers” which maintain information about a large number of resources having the required characteristics. Simulation analysis proves that the combined use of the resource mapping protocol (ARMAP) and the resource discovery protocol (ARDIP) allows users to find many useful results in a small amount of time.
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References
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Santa Fe Institute Studies in the Sciences of Complexity (1999)
Crespo, A., Garcia-Molina, H.: Routing indices for peer-to-peer systems. In: Proc. of the 2nd International Conference on Distributed Computing Systems (ICDCS 2002), Vienna, Austria, pp. 23–33 (2002)
Dasgupta, P.: Intelligent Agent Enabled P2P Search Using Ant Algorithms. In: Proc. of the 8th International Conference on Artificial Intelligence, Las Vegas, NV, pp. 751–757 (2004)
Van Dyke Parunak, H., Brueckner, S.A., Matthews, R., Sauter, J.: Pheromone Learning for Self-Organizing Agents. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 35(3) (2005)
Forestiero, A., Mastroianni, C., Spezzano, G.: A Multi Agent Approach for the Construction of a Peer-to-Peer Information System in Grids. In: Proc. of the 2005 International Conference on Self-Organization and Adaptation of Multi-agent and Grid Systems, SOAS 2005, Glasgow, Scotland (2005)
Lv, C., Cao, P., Cohen, E., Li, K., Shenker, S.: Search and replication in unstructured peer-to-peer networks. In: ACM, Sigmetrics (2002)
Mastroianni, C., Talia, D., Verta, O.: A Super-Peer Model for Resource Discovery Services in Large-Scale Grids. Future Generation Computer Systems 21(8), 1235–1456 (2005)
Petersen, K., Spreitzer, M., Terry, D., Theimer, M., Demers, A.: Flexible Update Propagation for Wakly Consistent Replication. In: Proc. of the 16th Symposium on Operating System Principles, pp. 288–301. ACM, New York (1997)
The Swarm environment, Swarm Development Group of Santa Fe University, New Mexico, http://www.swarm.org
Tsoumakos, D., Roussopoulos, N.: Adaptive probabilistic search for peer-to-peer networks. In: Third International Conference on Peer-to-Peer Computing, P2P 2003, Linkoping, Sweden, pp. 102–110 (2003)
Tsoumakos, D., Roussopoulos, N.: A Comparison of Peer-to-Peer Search Methods. In: Proc. of the Sixth International Workshop on the Web and Databases WebDB, San Diego, CA, pp. 61–66 (2003)
Yang, B., Garcia-Molina, H.: Efficient search in peer-to-peer networks. In: Proc. of ICDCS, Wien, Austria (2002)
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Forestiero, A., Mastroianni, C., Spezzano, G. (2006). An Agent Based Semi-informed Protocol for Resource Discovery in Grids. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758549_139
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DOI: https://doi.org/10.1007/11758549_139
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