Natural Computing: Performance Analysis of Evolutionary Algorithms for Task Scheduling in Cloud Environment

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-58 Number-1
Year of Publication : 2018
Authors : D. Sumathi, Dr. P. Poongodi
  10.14445/22312803/IJCTT-V58P103

MLA

D. Sumathi, Dr. P. Poongodi , "Natural Computing: Performance Analysis of Evolutionary Algorithms for Task Scheduling in Cloud Environment". International Journal of Computer Trends and Technology (IJCTT) V58(1):20-24, April 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Cloud is ubiquitous, convenient virtual environment having pool of heterogeneous resources to provide services through Internet on pay-per-use, on-demand and at-scale basis. Cloud Scheduling algorithms used allocate ready tasks to available resources at affordable time to provide quality services to cloud users. Allocating resources in heterogeneous and geographically distributed environment is NP-hard. Many swarm based meta heuristic algorithms have been proposed by various researchers to solve these problems. In this paper, we analyse some Natural Computing Algorithms which inspired by the social behaviour of animals, birds and insects to solve complex mathematical problems and provides better solution.

References
[1] Salot, P 2013, „A Survey of Various Scheduling Algorithm in Cloud Computing Environment‟. International Journal of research and engineering Technology (IJRET), ISSN, pp. 2319-1163.
[2] Mohialdeen, IA 2013, „Comparative Study of Scheduling Algorithms in Cloud Computing Environment‟. Journal of Computer Science, vol. 9, no. 2, p. 252
[3] D. Sumathi and P. Poongodi, Scheduling Based on Hybrid Particle Swarm Optimization with Cuckoo Search Algorithm in Cloud Environment, IIOAB JOURNAL 7 (9), 358-366, 2016
[4] Gupta, H., Singh, D., & Gupta, B. K. Scheduling Techniques in Cloud Computing: A Systematic Review
[5] Tawfeek, MA, El-Sisi, A, Keshk, AE & Torkey, FA 2013, „Cloud Task Scheduling Based on Ant Colony Optimization‟. In Computer Engineering & Systems (ICCES), 8th International Conference, IEEE, pp. 64-69
[6] D. Sumathi and P. Poongodi, Secure Medical Information Processing in Cloud: Trust with Swarm Based Scheduling, Journal of Medical Imaging and Health Informatics Vol. 6, 1636–1640, 2016
[7] Pandey, S, Wu, L, Guru, SM & Buyya, R 2010, „A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments‟. In Advanced information networking and applications (AINA), 24th IEEE international conference, IEEE, pp. 400-407
[8] Xin-She Yang, Bat Algorithm: Literature Review and Appliation‟, International Journal of Bio inspired computation, vol. 5, No. 3, 2013
[9] Xin-She Yang, „Natural Inspired Meta Heuristics Algorithms‟, Luniver Press, ISBN:1905986106 9781905986101, 2008
[10] Beni, G., Wang, J. Swarm Intelligence in Cellular Robotic Systems, Proceed. NATO Advanced Workshop on Robots and Biological Systems, Tuscany, Italy, June 26–30 (1989)

Keywords
Cloud Computing, Scheduling Algorithm, Natural Computing.