Abstract
Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.
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References
S. Parsa, and O. Bushehrian, "Performance-Driven Object-Oriented Program Remodularization", ISSN: 1751-8806, INSPEC Accession Number: 10118318, Digital Object Identifier: 10.1049/iet-sen: 20070065, Aug, 2008.
S. Parsa, and V. Khalilpoor, "Automatic Distribution of Sequential Code Using JavaSymphony Middleware", 32th International Conference On Current Trends in Theory and Practice of Computer Science, 2006.
Roxana Diaconescu, Lei Wang, Zachary Mouri, and Matt Chu, "A Compiler and Runtime Infrastructure for Automatic Program Distribution", 19th International Parallel and Distributed Processing Symposium (IPDPS 2005), IEEE, 2005.
S. Parsa, O. Bushehrian, "The Design and Implementation of a Tool for Automatic Software Modularization", Journal of Supercomputing, Volume 32, Issue 1, April 2005.
Mohammad M. Fuad, and Michael J. Oudshoorn, "AdJava-Automatic Distribution of Java Applications", 25th Australasian Computer Science Conference (ACSC2002), Monash University, Melbourne, 2002.
S. Mitchell Brian, "A Heuristic Search Approach to Solving the Software Clustering Problem", Thesis, Drexel University, March 2002.
Thomas Fahringer, and Alexandru Jugravu, "JavaSymphony: New Directives to Control and Synchronize Locality, Parallelism, and Load Balancing for Cluster and GRID-Computing", Proceedings of Joint ACM Java Grande ISCOPE 2002 Conference, Seattle, Washington, Nov 2002.
Michiaki Tatsubori, Toshiyuki Sasaki, Shigeru Chiba1, and Kozo Itano, "A Bytecode Translator for Distributed Execution of Legacy Java Software", LNCS 2072, pp. 236-255, 2001.
Markus Dahm, "Doorastha—A Step Towards Distribution Transparency", JIT, 2000.
Michael Philippsen, and Bernhard Haumacher, "Locality Optimization in JavaParty by Means of Static Type Analysis", Concurrency: Practice & Experience, pp. 613-628, July 2000.
Andre Spiegel, "Pangaea: An Automatic Distribution Front-End for Java", 4th IEEE Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS '99), San Juan, Puerto Rico, April 1999.
Saeed Parsa, and Omid Bushehrian, "Genetic Clustering with Constraints", Journal of Research and Practice in Information Technology, 2007.
Leng Mingwei, Tang Haitao, and Chen Xiaoyun, "An Efficient K-means Clustering Algorithm Based on Influence Factors", Eighth ACIS Int. Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, pp. 815-820, July 2007.
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, and Angela Y. Wu, "An Efficient K-Means Clustering Algorithm: Analysis and Implementation", IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 24, No. 7, July 2002.
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, and Angela Y. Wu, "The Analysis of a Simple K-Means Clustering Algorithm", Proc. of the Sixteenth Annual Symposium on Computational Geometry, pp. 162, June 2000.
B. Hendrickson, and R. Leland, "A Multilevel Algorithm for Partitioning Graphs", Proceedings of the 1995 ACM/IEEE Conference on Supercomputing (CDROM), pp. 28, ACM Press, 1995.
K. A. Dejong , and W. M. Spears, "Using Genetic Algorithms to Solve NP-Complete Problems", Proceedings of the Third International Conference on Genetic Algorithms, 1989.
K. S. Narendra, and M. A. L. Thathachar, "Learning Automata: An Introduction", Prentice-hall, Englewood cliffs, 1989.
M. R. Meybodi, and H. Beigy, "Solving Graph Isomorphism Problem by Learning Automata", Thesis, Computer Engineering Faculty, Amirkabir Technology University, Tehran, Iran, 2000.
H. Beigy, and M. R. Meybodi, "Optimization of Topology of Neural Networks Using Learning Automata", Proceedings of 3th Annual International Computer Society of Iran Computer Conference (CSICC-98), Tehran, Iran, pp. 417-428, 1999.
B. J. Oommen, R. S. Valiveti, and J. R. Zgierski, "An Adaptive Learning Solution to the Keyboard Optimization Problem", IEEE Transaction On Systems. Man. And Cybernetics, Vol. 21, No. 6, pp. 1608-1618, 1991.
B. J. Oommen, and D. C. Y. Ma, "Deterministic Learning Automata Solution to the Keyboard Optimization Problem", IEEE Transaction on Computers, Vol. 37, No. 1, pp. 2-3, 1988.
A. A. Hashim, S. Amir, and P. Mars, "Application of Learning Automata to Data Compression", in Adaptive and Learning Systems, K. S. Narendra, Editor, New York, Plenum Press, pp. 229-234, 1986.
M. R. Meybodi, and S. Lakshmivarhan, "A Learning Approach to Priority Assignment in a Two Class M/M/1 Queuing System with Unknown Parameters", Proceedings of Third Yale Workshop on Applications of Adaptive System Theory, Yale University, pp. 106-109, 1983.
Bager Zarei, M. R. Meybodi, and Mortaza Abbaszadeh, "A Hybrid Method for Solving Traveling Salesman Problem", Proceedings of the 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), IEEE Computer Society, Melbourne, Australia, pp. 394-399, 11-13 July 2007.
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Abofathi, Y., Zarei, B., Parsa, S. (2010). Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph. In: Sobh, T., Elleithy, K. (eds) Innovations in Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9112-3_35
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DOI: https://doi.org/10.1007/978-90-481-9112-3_35
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