Abstract
Recent researches in distributed system include intelligent resource finding, dynamic replication and adaptive load balancing schemes which focus on improving specific technique. In this paper, an intelligent distributed framework is presented to address the use of intelligent models for adaptive distributed object groups. Moreover, this paper proposes the agent-based data-mining model for implementing adaptive schemes using data mining algorithms and efficient interactions using multi-agent system. The k-means algorithm constructs group classes of object, multilayer perceptron classifies the client requests using the classes constructed from k-means and patterns generated from Apriori algorithm determine the next object needed to be replicated. For efficient interactions, the data mining is modeled in multi-agent system. Simulation result using the proposed model shows great improvements on serving clients by minimizing delay time and optimizes system performance by efficient load distribution.
This research was supported by the Program for the Training of Graduate Students in Regional Innovation which was conducted by the Ministry of Commerce Industry and Energy of the Korean Government.
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References
Coulouris, G., Dollimore, J., Kinderberg, T.: Distributed Systems Concepts and Design, 4th edn., pp. 1–25. Addison-Wesley, Reading (2005)
Badidi, E., Keller, R.K., Kropf, P.G., Van Dongen, V.: The Design of a Trader-based CORBA Load Sharing Service. In: Proc. of the 12th International Conference on Parallel and Distributed Computing Systems, pp. 75–80 (1999)
Van Steen, M., Ballintijn, G.: Achieving Scalability in Hierarchical Location Services. In: Proc. of the 26th International Computer Software and Applications Conference (2002)
Felber, P., Guerraoui, R.: Programming with Object Groups in CORBA. Concurrency, IEEE 8(1), 48–58 (2000)
Felber, P., Guerraoui1, R., Schiper, A.: Replication of CORBA Objects. Advances in Distributed Systems: Advanced Distributed Computing: From Algorithms to Systems, 254 (2000)
Othman, O., O’Ryan, C., Schmidt, D.C.: The Design of an Adaptive CORBA Load Balancing Service. IEEE Distributed Systems Online 2 (4) (2001)
Kwok, Y.K., Cheung, L.S.: A New Fuzzy-decision based Load Balancing System for Distributed Object Computing. Journal of Parallel and Distributed Computing 2(64), 238–253 (2004)
Han, J., Kamber, M.: Data Mining Concepts and Techniques, 2nd edn., pp. 1–38. Morgan Kaufmann, San Francisco (2006)
Ferber, J.: Multi-Agent Systems An Introduction to Distributed Artificial Intelligence, pp. 307–340. Addison-Wesley, Reading (1999)
Hendler, J.: Introduction to the Special Issue: AI, agents, and the Web. Intelligent Systems, IEEE 21(1), 11–11 (2006)
Yang, L., Wang, F.Y.: Driving into Intelligent Spaces with Pervasive Communications. Intelligent Systems, IEEE 22(1), 12–15 (2007)
Marik, V., McFarlane, D.: Industrial Adoption of Agent-based Technologies. Intelligent Systems, IEEE 20(1), 27–35 (2005)
Pechoucek, M., Thompson, S.G., Baxter, J.W., Horn, G.S., Kok, K., Warmer, C., Kamphuis, R., Maric, V., Vrba, P., Hall, K.H., Maturana, F.P., Dorer, K., Calisti, M.: Agents in Industry: The Best from The AAMAS 2005 Industry Track. Intelligent Systems, IEEE 21(2), 86–95 (2006)
Anderberg, M.R.: Cluster Analysis for Applications. Academic Press, New York (1973)
MacDougall, M.H.: Simulating Computer Systems Techniques and Tools, pp. 16–17. The MIT Press, Cambridge (1983)
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Mateo, R.M.A., Yoon, I., Lee, J. (2008). Data-Mining Model Based on Multi-agent for the Intelligent Distributed Framework. In: Nguyen, N.T., Jo, G.S., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2008. Lecture Notes in Computer Science(), vol 4953. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78582-8_76
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DOI: https://doi.org/10.1007/978-3-540-78582-8_76
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