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Application of Meta Heuristic Algorithm for Real Time Task Assignment Problem on Heterogeneous Processor

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IJCA Proceedings on National Conference on Information and Communication Technologies
© 2015 by IJCA Journal
NCICT 2015 - Number 1
Year of Publication: 2015
Authors:
Poongothai M.
Rajeswari A.
Umer Farook K. A.

Poongothai M., Rajeswari A. and Umer Farook K.a.. Article: Application of Meta Heuristic Algorithm for Real Time Task Assignment Problem on Heterogeneous Processor. IJCA Proceedings on National Conference on Information and Communication Technologies NCICT 2015(1):13-18, September 2015. Full text available. BibTeX

@article{key:article,
	author = {Poongothai M. and Rajeswari A. and Umer Farook K.a.},
	title = {Article: Application of Meta Heuristic Algorithm for Real Time Task Assignment Problem on Heterogeneous Processor},
	journal = {IJCA Proceedings on National Conference on Information and Communication Technologies},
	year = {2015},
	volume = {NCICT 2015},
	number = {1},
	pages = {13-18},
	month = {September},
	note = {Full text available}
}

Abstract

Multiprocessor real-time task assignment algorithm helps in the design and implementation of real time systems. Assigning real time task to heterogeneous multiprocessor system is challenging problem because the performance of each task varies from one processor to another. As the result of this determining solution for assigning task in heterogeneous processor leads to an NP hard problem. In this paper, Hybrid Ant Colony Optimization incorporated with Tabu search algorithm [HACO_TS] is proposed for real time task assignment in the heterogeneous system. The proposed Max-Min Ant System is included with a Tabu search algorithm to improve task assignment solution without exceeding the processors computing capacity and fulfilling the dead line constraints. From the experimental results, the proposed algorithm achieved better utilization compared to random assignment algorithm.

References

  • T. Braun, et al. , "A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing system", Journal of Parallel and Distributed computing Vol. 61, pp810-837,2001.
  • Chen, H. , A. M. K. Cheng and Y. W. Kuo, "Assigning real-time tasks to heterogeneous processors by applying ant colony optimization", J. Parallel Distributed Computing, 71: 132-142, 2011.
  • T. Vetiselvan, P. Chitra, Dr. P. Venkatesh, "parallel implementation of task scheduling using Ant Colony Optimization",International Journal of Recent Trends in Engineering,Vol. 1. No. 1. may 2009.
  • HyunJin Kim, Sungho Kang, "Communication-aware task scheduling and voltage selection for total energy minimization in a multiprocessor system using Ant Colony Optimization", information sciences 181, pp 3995-4008, 2011.
  • Qinma Kang, Hong He, "Honeybee Mating Optimization algorithm for Task assignment in heterogeneous ccomputing systems", Intelligent Automation & soft Computing, 12 July 2013.
  • M. B. Abdelhalim, "Task assignment for heterogeneous multiprocessors using Re-Excited Particle Swarm Optimization", International Conference on computer and Electrical Engineering, pp 23-27, 2008.
  • Albert M. K. , Cheng, Real-Time Systems: Scheduling, Analysis, and Verification, University of Houston, John Wiley & Sons, 2002.
  • Peng-Yeng Yin, Shiuh-Sheng Yu, Pei-Pei Wang, Yi-Te Wang, "A hybrid particle swarm optimization algorithm for optimal task assignment in distributed systems", Computer Standards & Interfaces, Vol. 28, pp. 441-450, 2006.
  • H. Chen, A. M. K. Cheng, Applying ant colony optimization to the partitionedscheduling problem for heterogeneous multiprocessors, WIP session, in: IEEERTAS, 2005.
  • Marco Dorigo and Thomas Stützle . , Ant ColonyOptimization, MIT PressCambridge, MassachusettsLondon, England 2004.
  • Ms. M. Poongothai, "ARM Embedded Web Server Based on DACS System", IEEE proceedings, International Conference on Process Automation, Control and Computing(ICPAC11), July 20-22, 2011.
  • K. Prescilla, A. Immanuel Selvakumar, "Modified Binary Particle Swarm optimization algorithm application to real-time task assignment in heterogeneous multiprocessor", Microprocessors and Microsystems Vol. 37, 583–589, 2013.
  • Umarani, G. Srikanth, "Tasks Scheduling using Ant Colony Optimization", Journal of Computer Science Vol. 8 (8): 1314-1320, 2012.
  • Hong Jin, Hui Wang, Hongan Wang, Guozhong Dai, "An ACO-Based Approach for Task Assignment and Scheduling of Multiprocessor Control Systems"Springer Berlin Heidelberg Proceedings, Third International Conference on Theory and Applications of Models of Computation(TAMC 2006), Beijing, China, May 15-20, pp 138-147, 2006.
  • Jian Wu, Xinxue Liu, JianshengShu, Yaxiong Li, Kaifeng Liu, "Independent Task Assignment of Space Warfare Based onMASand ACO", Journal of Information & Computational Science 10:12 3861- 3867, 2013.
  • M. ,Dorigo, V. , Maniezzo and A. , Colorni, "Ant System: Optimization by a colony of cooperating agents", IEEE. T. Syst. Man. Cyb. PartB26, no. 1, 29–41, 1996.
  • M. , Dorigo and L. M. , Gambardella, "Ant Colony System: A cooperative learning approach to the traveling salesman problem", IEEE. T. Evolut. Comput. 1, no. 1, 53–66, 1997.