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An Upgraded Algorithm of Resource Scheduling using PSO and SA in Cloud Computing

International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 74 - Number 8
Year of Publication: 2013
Talwinder Kaur
Seema Pahwa

Talwinder Kaur and Seema Pahwa. Article: An Upgraded Algorithm of Resource Scheduling using PSO and SA in Cloud Computing. International Journal of Computer Applications 74(8):28-32, July 2013. Full text available. BibTeX

	author = {Talwinder Kaur and Seema Pahwa},
	title = {Article: An Upgraded Algorithm of Resource Scheduling using PSO and SA in Cloud Computing},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {74},
	number = {8},
	pages = {28-32},
	month = {July},
	note = {Full text available}


Cloud computing is a subscription-based service whose primary benefit is application scalability which allows real-time provisioning of resources to meet application requirements. Scheduling is the most prominent issue in cloud computing. Generally the goal of scheduling is to properly dispatch parallel jobs to slave node machines according to different scheduling policies. In this paper previously existing algorithms i. e. Particle Swarm Optimization (PSO), Improved Particle Swarm Optimization (IPSO), Simulated Annealing (SA) Algorithm, and Hybrid Particle Swarm Optimization-Simulated Annealing based on utilization time are studied which were proposed to handle problems posed by network properties between user and resources. A new algorithm is designed using shortest path theory, Particle Swarm Optimization and Simulated Annealing technique which achieve the target consuming less average execution time to obtain more efficiency in resource utilization and minimize the cost of the processing.


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