Abstract
Grid computing provides infrastructure for solving distributed problem by sharing, selection and aggregation of distributed resources at runtime depending on their availability, performance, cost and user’s quality of service requirements. Utilization of this powerful technology is mainly conditioned by tricky management of different architectures and environments and by the difficulty to identify an efficient resource selection to map tasks into grid resources that dynamically vary their features. Resources selection needs of intelligence based automatic workflow generation to predict optimal run-time jobs allocation. In this paper we propose a dynamic job run-time scheduling system based on Java and fuzzy technology to manage Grid resources and minimize human interaction in scheduling grid jobs.
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Chandy, K., Dimitron, B., Le, H., Mandleson, J., Richardson, M., Rifkin, S.A., Tawaka, P.W., Weisman L.: A world-wide distributed system using java and the internet. In: Proceedings of the 5th IEEE Internation Symposium on High Performance Distributed Computing. IEEE HPDCS (1996)
Fox, G., Formaski, W.: Towards web/java based high performance distributed computing – and evolving virtual machine. In: Proceedings of the 5th IEEE Internation Symposium on High Performance Distributed Computing. IEEE HPDCS (1996)
Guerriero, A., Pasquale, C., Ragni, F.: Resources and Jobs Fuzzy Classification in a Java Based Grid Architecture. In: Proceeding of CIMSA 2009 - IEEE International Conference on Computational Intelligence for Measurement System and Applications, Hong Kong, China, May 11-13 (2009)
Guerriero, A., Pasquale, C., Ragni, F.: Java based architecture for Grid Application. In: Proceeding of VECIMS 2009 - IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems May, Hong Kong, China, pp. 11–13 (2009)
Guo, D., Hu, L., Jin, S., Guo, B.: Applying Preference-based Fuzzy Clustering Technology to Improve Grid Resources Selection Performance - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007 (2007)
Hu, L., Guo, D., Che, X.: A Fast Resource Selection Approach for Grid Applications Based on Fuzzy Clustering Technology. In: The 10th IEEE International Conference on High Performance Computing and Communications
Li, F., Qi, D.: Research on Grid Resource Allocation Algorithm Based on Fuzzy Clustering. In: Second International Conference on Future Generation Communication and Networking
Lu, B., Chen, J.: Grid Resource Scheduling Based on Fuzzy Similarity Measures. In: 3rd IEEE International Conference on Cybernetics and Intelligent Systems (CIS), June 3- 6 (2008)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Fransisco (2006)
Everitt, B.S., Landau, S., Leese, M.: Clustering Analysis. Oxford University Press, Oxford
Dabhi, V.K., Prajapati, H.B.: Soft Computing Based Intelligent Grid Architecture. In: Proceedings of the International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia, May 2008, pp. 13–15 (2008)
Gui, X.L., Wang, Q.J., Gong, W.Q., Qiang, D.P.: Study of a Machine Selection Algorithm for Grid Computing. Journal of Computer Research and Development, Peking 2004-12, 2189–2194 (2004)
Di Lecce, V., Pasquale, C., Piuri, V.: Agent-Based Communication for an Environmental Monitoring Application. In: 14th International Conference on Computer Theory and Application, ICCTA 2004, Alexandria Egypt, September, CD-Rom version, pp. 28–30 (2004)
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Guaragnella, C., Guerriero, A., Pasquale, C.C., Ragni, F. (2009). Jobs Run-Time Scheduling in a Java Based Grid Architecture. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_51
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DOI: https://doi.org/10.1007/978-3-642-04070-2_51
Publisher Name: Springer, Berlin, Heidelberg
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