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Dynamic Load Balancing in Grid Computational Environment using Ant Algorithm

Published on August 2016 by Sugandha Satija
journal_cover_thumbnail

Advanced Computing and Information Technology
Foundation of Computer Science USA
TACIT2016 - Number 1
August 2016
Authors: Sugandha Satija
063aab26-f300-49e5-be04-be942e192667

Sugandha Satija . Dynamic Load Balancing in Grid Computational Environment using Ant Algorithm. Advanced Computing and Information Technology. TACIT2016, 1 (August 2016), 1-3.

@article{
author = { Sugandha Satija },
title = { Dynamic Load Balancing in Grid Computational Environment using Ant Algorithm },
journal = { Advanced Computing and Information Technology },
issue_date = { August 2016 },
volume = { TACIT2016 },
number = { 1 },
month = { August },
year = { 2016 },
issn = 0975-8887,
pages = { 1-3 },
numpages = 3,
url = { /proceedings/tacit2016/number1/25827-it32/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Advanced Computing and Information Technology
%A Sugandha Satija
%T Dynamic Load Balancing in Grid Computational Environment using Ant Algorithm
%J Advanced Computing and Information Technology
%@ 0975-8887
%V TACIT2016
%N 1
%P 1-3
%D 2016
%I International Journal of Computer Applications
Abstract

Load Balancing is one of the major issues in computational Grids. Research has proved that load balancing on Grid Computational Environment is best solved by Heuristic approach. The main motive behind load balancing is to equally spread the load on each node of the Grid. In this paper, ASRank (Rank based Ant system) is proposed to provide shortest path from PE (Processing element) to RN (Resource node) while balancing the load on each RN. ASRank will determine the best resource to be allocated to the jobs, based on their paths as well as their load. ASRank reads the pheromone value, such that solutions with shorter paths will have higher pheromone value. This pheromone value is used by other PE's with the help of a process named as Stigmergy, to reach to the RN. This will maximize the efficiency of the Grid and will result in high throughput. Thus, it increases the performance in the Grid Computational Environment.

References
  1. Sowmya Suryadevera, Jaishri Chourasia, Sonam Rathore and Abdul Jhummarwala "Load Balancing in Computational Grids Using Ant Colony Optimization Algorithm "International Journal of Computer and Communication Technology ISSS(online): 2231-0371 vol-3,iss- 3,2012.
  2. Sandip Kumar Goyal and Manpreet Singh "adaptive and Dynamic load balancing in Grid using Ant Colony Optimization" International Journal of Engineering and Technology(IJET).
  3. D. Maruthanayagam and Dr. R. Uma Rani "Enhanced Ant colony algorithm for Grid Scheduling" International Journal of Computer Technology and Applications. Vol1 (1) 43-53.
  4. P. McMullen and P. Tarasewich, "Using ant techniques to solve the assembly line balancing problem," Institute of Industrial Engineers Trans. , vol. 35, no. 7, pp. 605-617, 2003.
  5. Jagdish Chandra Patni, Dr. M. S. Aswal, Om Prakash Pal and Ashish Gupta, "Load balancing Strategies for Grid Computing" presented at 3rd international conference on electronics computer technology (ICECT), vol. 3, pp. 239- 243, 2011.
  6. S. Fidanova and M. Durchova, "Ant algorithm for grid scheduling problem," Lecture Notes in Computer Science, vol. 3743, pp. 405- 412, 2006.
  7. A. Ali, M. A. Belal and M. B. Al-Zoubi, "Load Balancingof Distributed system Based on Multiple Ant ColoniesOptimization,"American Journal of Applied Sciences, vol. 7(3), pp. 433-438, 2010.
  8. K. Sathish and A. Reddy, "Enhanced ANT Algorithm Based Load Balanced Task Scheduling in GRID Computing," IJCSNS, vol. 8, pp. 219, 2008.
  9. S. K. Goyal, R. B. Patel, and M. Singh, "Adaptive and dynamic load balancing methodologies for distributed environment: a review," International Journal of Engineering Science and Technology (IJEST), vol. 3, no. 3, pp. 1835-1840, 2011.
  10. H. Yan, X. Shen, X. Li, and M. Wu, "An improved ant algorithm for job scheduling in grid computing," in Proc. 4th Inter. Conf. Machine Learning and Cybernetics, 2005, pp. 2957-2961.
  11. H. J. A. Nasir, K. R. K. Mahamud, and A. M. Din, "Load balancing using enhanced ant algorithm in grid computing," in Proc. 2nd Inter. Conf. Computational Intelligence, Modelling and Simulation, 2010, pp. 160-165.
  12. A. D. Ali, and M. A. Belal, "Multiple ant colonies optimization for load balancing in distributed systems," in Proc. Inter. Conf. (ICTA'07), 2007.
  13. Dushyant Vaghela "An Advanced Approach On Load Balancing in Grid Computing"
  14. Nima Jafari Navimipour, Seyes Hasan Es-hagi, "LGR: The New Genetic Based Scheduler for Grid Computing Systems",International Journal of Computer and Electrical Engineering, Vol. 1, No. 5, December, 2009, pp. 1793-8163.
  15. U. Karthick Kumar "A Dynamic Load Balancing Algorithm in Computational Grid Using Fair Scheduling" IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 1,September 2011
Index Terms

Computer Science
Information Sciences

Keywords

Grid Computing Load Balancing Asrank Ant Algorithm Processing Element Resource Node Stigmergy Pheromone Value