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International Journal of Computer Applications Technology and Research (IJCATR)

Volume 1 Issue 2 Sept-October 2012

Task Scheduling Heuristic in Grid Computing

Ashish Chandak, Bibhudatta Sahoo and Ashok Kumar Turuk

10.7753/IJCAT0102.1002

    
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Keywords: Task Scheduling, Simple Heuristic, Economic Heuristic, Iterative Heuristic.

Abstract References BibText Highlights

        Task scheduling is heart of any grid application which guides resource allocation in grid. Heuristic task scheduling strategies have been used for optimal task scheduling. Heuristic techniques have been widely used by the researchers to solve resource allocation problem in grid computing. In this paper, we classify heuristic task scheduling strategies in grid on the basis of their characteristics. We identified different types of heuristics such as population based heuristic, economic heuristic, meta heuristic, simple heuristic, and hybrid heuristic.

    1. Oppenheimer DM. Shah AK. Heuristics made easy: an effort-reduction framework. Psychol. Bull.
    2. Kousalya.K and Balasubramanie.P. Ant Algorithm for Grid Scheduling Powered by Local Search. International Journal of Open Problems in Computer
    3. R. Buyya, D. Abramson, J. Giddy, and H. Stockinger.Economic Models for Resource Management and Scheduling in Grid Computing. The Journal of Concurrency and Computation, 14:1507-1542, 2002.
    4. Ni L.M. Zhiwei Xu Lijuan Xiao, Yanmin Zhu. Incentive based Scheduling for Market Like Computational Grids. IEEE Transactions on Parallel and Distributed Systems, 19:903-913, 2008.
    5. Preetam Ghosh, Nirmalya Roy, Sajal K. Das, and Kalyan Basu. A Pricing Strategy for Job Allocation in Mobile Grids using a Non-cooperative Bargaining Theory Framework. Journal of Parallel and Distributed Computing, 65(11):1366 - 1383, 2005.
    6. B. Pourebrahimi, K. Bertels, G.M. Kandru, and S.Vassiliadis. Market Based Resource Allocation in Grids.e-Science and Grid Computing, International Conference on, 2006.
    7. Yang Gao, Hongqiang Rong, and Joshua Zhexue Huang.Adaptive Grid Job Scheduling with Genetic Algorithms.Future Generation Computer Systems, 21(1):151 - 161,2005.
    8. Fatos Xhafa, Enrique Alba, Bernab Dorronsoro, and Bernat Duran. Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms. Journal of Mathematical Modelling and Algorithms, 7:217-236,2008.
    9. Yuan-Shun Dai and Xiao-Long Wang. Optimal Resource Allocation on Grid Systems for Maximizing Service Reliability using a Genetic Algorithm. Reliability Engineering and System Safety, 91(9):1071 - 1082, 2006
    10. C. Fayad, J.M. Garibaldi, and D. Ouelhadj. Fuzzy Grid Scheduling Using Tabu Search. In Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International, pages 1 -6, july.
    11. Lei Zhang, Yuehui Chen, and Bo Yang. Task Scheduling Based on PSO Algorithm in Computational Grid.International Conference on Intelligent Systems Design and Applications, 2:696-704, 2006.
    12. Li Liu, Yi Yang, Lian Li, and Wanbin Shi. Using Ant Colony Optimization for Superscheduling in Computational Grid. In Services Computing, 2006. APSCC '06. IEEE Asia Pacific Conference on, pages 539- 545, dec. 2006.
    13. S. Fidanova. Simulated Annealing for Grid Scheduling Problem. In IEEE International Symposium on Modern Computing, 2006. John Vincent Atanaso, 2006 (JVA '06)
    14. Ruay-Shiung Chang, Jih-Sheng Chang, and Po-Sheng Lin. An Ant Algorithm for Balanced Job Scheduling in Grids. Future Generation Computer Systems, 25(1):20 -27, 2009.
    15. L.M. Gambardella M. Dorigo. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation, 1:53 - 66, 1997.
    16. T. Stutzle. MAX-MIN Ant System for Quadratic Assignment Problems. Technical Report,Intellectics Group, Department of Compute Science, Darmstadt,University of Technology, Germany, 1997.
    17. C. Strauss B. Bullnheimer, R.F. Hartl. A New Rankbased Version of the Ant System. Central European Journal for Operations Research and Economics, 1:25 -38, 1999.
    18. L.M. Gambardella E.D. Taillard. Adaptive Memories for the Quadratic Assignment Problem. Technical Report IDSIA-87-97, IDSIA, Lugano, Switzerland, 1997.
    19. A. Colorni M. Dorigo, V. Maniezzo. The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics, 26:29 -41, 1996.
    20. Zhihui Du, Man Wang, Yinong Chen, Yin Ye, and Xudong Chai. The Triangular Pyramid Scheduling Model and Algorithm for PDES in Grid. Simulation Modelling Practice and Theory, 17(10):1678 - 1689, 2009.
    21. Wei wei JIANG, Hong yan CUI, and Jian ya CHEN. A Fuzzy Modeling based Dynamic Resource Allocation Strategy in Service Grid. The Journal of China Universities of Posts and Telecommunications, 16:108 - 113, 2009.
    22. Jingbo Yuan, Shunli Ding, and Cuirong Wang. Tasks Scheduling Based on Neural Networks in Grid. In Third International Conference on Natural Computation, 2007.ICNC 2007., volume 3, pages 372 -376, aug. 2007.
    23. X. Wang Y.M. Teo and J.P. Gozali. A Compensation based Scheduling Scheme for Grid Computing. In Proceedings of the Seventh International Conference on High Performance Computing and Grid in Asia Pacific Region, 2004.
    24. Fatos Xhafa, Juan Gonzalez, Keshav Dahal, and Ajith Abraham. A GA(TS) Hybrid Algorithm for Scheduling in Computational Grids. In Hybrid Artificial Intelligence Systems, volume 5572 of Lecture Notes in Computer Science, pages 285-292. Springer Berlin / Heidelberg,2009.
    25. Ajith Abraham, Rajkumar Buyya, and Baikunth Nath.Nature's Heuristics for Scheduling Jobs on Computational Grids. In in Proc. of 8th IEEE International Conference on Advanced Computing and Communications (ADCOM 2000), pages 45-52, 2000.
    26. Hao Tian. A New Resource Management and Scheduling Model in Grid Computing Based on a Hybrid Genetic Algorithm. In Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on, volume 3, pages 113 -117, 2008.
    27. Wanneng Shu, Shijue Zheng, Li Gao, and Xiong Wang.An Hybrid Evaluative Algorithm Applied to Task Scheduling. In International Conference on Communications, Circuits and Systems Proceedings,2006, volume 3, pages 2070 - 2073, june 2006.
    28. J. Kolodziej and F. Xhafa. A Game-Theoretic and Hybrid Genetic Meta-Heuristics Model for Security- Assured Scheduling of Independent Jobs in Computational Grids. In Complex, Intelligent and Software Intensive Systems (CISIS), 2010 International Conference on", month="February", pages="93 -100", year="2010".
    29. Yuan-Shun Dai and Xiao-Long Wang. Optimal Resource Allocation on Grid Systems for Maximizing Service Reliability using a Genetic Algorithm. Reliability Engineering and System Safety, 91(9):1071 - 1082,2006.
    30. Helen D. Karatza Sofia K. Dimitriadou. Multi-Site Allocation Policies on a Grid and Local Level. Electronic Notes in Theoretical Computer Science, 261:163 - 179,2010.

@article{ashish01021002,
title = "Agent based Task Scheduling in Grid",
journal = "International Journal of Computer Applications Technology and Research",
volume = "1",
number = "2",
pages = "49 - 52",
year = "2012",
author = "Ashish Chandak, Bibhudatta Sahoo and Ashok Kumar Turuk",
}

Heuristic task scheduling strategies have been used for optimal task scheduling.
Simulation application for Agent based Task Scheduling in Grid is developed in MATLAB.