Grid scheduling: Comparative study of MACO & TABU search
Keywords:
Grid Computing, job scheduling, ACO, MACO, tabu searchAbstract
Grid computing is progressively considered as a Next-generation computational platform that supports wide-area parallel and distributed computing. Scheduling jobs to resources in grid computing is difficult due to the distributed and heterogeneous nature of the resources. In Grid computing finding optimal schedules for such an environment is (in general) an NP-hard problem, and so heuristic technique must be used. The aim of grid task scheduling is to achieve high system throughput and to distribute various computing resources to applications. Many different algorithms have been proposed to solve this problem. Some of these algorithms are based on heuristic techniques that provide an Optimal or near optimal solution for large grids.In this paper shows the grid scheduling algorithms and comparison between them.
References
S.Umarani1, L.M.Nithya, A.Shanmugam,Efficient Multiple Ant Colony Algorithm for Job Scheduling In Grid Environment,S. Umarani et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (2).
Ku Ruhana Ku-Mahamud andHusna Jamal Abdul Nasir, ―Ant Colony Algorithm for Job Scheduling in Grid Computing,2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.
Ting-ting Zhao, Ting Liu,Analysis of the Hybrid Scheduling Algorithm in the Gird Environment,Proceedings of 2012 International Conference on Modelling, Identification and Control, Wuhan, China, June 24-26, 2012.
Youchan Zhu, Qiujuan Wei,An Improved Ant Colony Algorithm for Independent Tasks Scheduling of Grid,Volumn 22010 IEEE.
JamshidBagherzadeh*, MojtabaMadadyarAdeh,An Improved Ant Algorithm for Grid Scheduling Problem, Proceedings of the 14th International CSI Computer Conference (CSICC'09)2009 IEEE
D.Maruthanayagam,Dr. R.Uma Rani,Enhanced ant colony system based on rasa algorithm in grid scheduling,Vol. 2 (4) , 2011, 1659-1674, International Journal of Computer Science and Information Technologies.
YizhiWang, Yuanxiang Ma, Grid Task Scheduling Based on Chaotic Ant Colony Optimization Algorithm, 2012 2nd International Conference on Computer Science and Network Technology.
Bing Tang, Yingying Yin, Quan Liu and Zude Zhou, Research on the Application of Ant Colony Algorithm in Grid Resource Scheduling,
MohdKamirYusof and MuhamadAzaharStapa, Achieving of Tabu Search Algorithm for Scheduling Technique in Grid Computing Using GridSim Simulation Tool: Multiple Jobs on Limited Resource, Vol. 3, No. 4, December, 2010, International Journal of Grid and Distributed Computing.
FatosXhafa, Javier Carretero, Bernab´eDorronsoro andEnrique Alba, A tabusearch algorithm for scheduling independent jobs in computational grids, Computing and Informatics, Vol. 28, 2009, 1001–1014, V 2009-Mar-2.
AysanRasooli, Mohammad Mirza-Aghatabar, SiavashKhorsandi, Introduction of Novel Dispatching Rules for Grid Scheduling Algorithms,May 13-15, 2008 Kuala Lumpur, Parameter MACO TABU MAKESPAN TIME 5755264 5761063 NET WATITING TIME 0.30394590 0.16991811 MACHINE USAGE 16hours 18 hours RESPONSE TIME 68025.85 66020.96 WEIGHT USAGE 54.38 54.28 RUN TIME 5.56 11.15 Malaysia, Proceedings of the International Conference on Computer and Communication Engineering 2008.
SonalNagariya, Mahendra Mishra, Manish Shrivastava, valume 87- no.6, February 2014, International Journal of Computer Application(0975- 8887).
Majid YOUSEFIKHOSHBAKHT, Mohammad SEDIGHPOUR, a combination of sweep algorithm and elite ant colony optimization for solving the multiple traveling salesman problem, Volume 13, Number 4/2012, pp. 295–301, proceedings of the romanian academy, series A.
Paola Pellegrini, Daniela Favaretto, Elena Moretti, Multiple Ant Colony Optimization for a Rich Vehicle Routing Problem: a Case Study.
FatosXhafa, Joanna Kołodziej, Leonard Barolli, Akli Fundo, A GA+TS Hybrid Algorithm for Independent Batch Scheduling in Computational Grids, 2011 International Conference on Network-Based Information Systems.
Bajeh, A. O., Abolarinwa, K. O., Optimization: A Comparative Study of Genetic and Tabu Search Algorithms, International Journal of Computer Applications (0975 – 8887) Volume 31–No.5, October 2011
Chang.R, Chang.J, and Lin.P "Balanced Job Assignment Basedon Ant Algorithm for Grid Computing," presented at Proceedings of the 2nd IEEE Asia-Pacific Service Computing Conference, 2007, pp. 291-295.
Foster and Kesselman.C, ―The Grid:Blueprint for a FutureComputing Infrastructure‖ Morgan Kaufman Publishers, USA, 1999.
Alba, E.—Almeida, F.—Blesa, M.—Cotta, C.—D´ıaz, M.—Dorta, I.—Gabarr´o, J.—Le´on, C.—Luque, G.—Petit, J.—Rodr´ıguez, C.—Rojas, A.—Xhafa, F.: Efficient parallel LAN/WAN algorithms for optimization.TheMallba project. Parallel Computing, Vol. 32, 2006, No. 5–6, pp. 415–440.
Ali, S.—Siegel, H.J.—Maheswaran, M.—Hensgen, D.—Ali, S.: RepresentingTask and Machine Heterogeneities for Heterogeneous Computing Systems. Tamkang Journal of Science and Engineering, Vol. 3, 2000, No. 3, pp. 195–207.
H¨ubscher, R.—Glover, F.: Applying Tabu Search With Influential Diversificationto Multiprocessor Scheduling. Comput. Oper. Res., Vol. 21, 1994, No. 8,pp. 877–884.
M. Chtepen, ―Dynamic scheduling in grids system,‖ Sixth Firw PhD Symposium, Faculty of Engineering, Ghent University, pp. 110, 2005.
Kousalya.K and Balasubramanie.P ,―An Enhanced Ant Colony Algorithm for Grid Scheduling Problem‖, IJCSNS International Journal of Computer Science and Network Security, Vol.8, No.4,2008
R.Thamilselvan and Dr.P.Balasubramanie, Integrating Genetic Algorithm, Tabu Search Approach for Job Shop Scheduling, Vol. 2, No. 1, 2009, International Journal of Computer Science and Information Security.
Maruthanayagam,Dr. R.Uma Rani,Enhanced ant colony system based on rasa algorithm in grid scheduling,CA:UniversityScience,1989.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2014 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
