e-ISSN : 0975-4024 p-ISSN : 2319-8613   
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ABSTRACT

ISSN: 0975-4024

Title : Comparison of Probabilistic Optimization Algorithms for Resource Scheduling in Cloud Computing Environment
Authors : Mayank Singh Rana, Sendhil Kumar KS, Jaisankar N
Keywords : Ant Colony, Genetic Algorithm, Optimization Techniques, Resource Scheduling, Swarm Intelligence.
Issue Date : Apr-May 2013
Abstract :
Cloud Computing has significantly made its landmark in the field of information technology. A concept which initially stood nebulous is now used as a synonym for internet. It has paved a way to increase capacity as well as add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software.“Cloud computing in broad sense can be understood as a connected pool of computing resources (including software and hardware) which can eventually be delivered as a service over a network (in broad sense the Internet)”. Resources are available to the user in utility-style infrastructure. However management of resources in a dynamic fashion stands a vast area for researchers. These resources are precisely available at certain fixed times and also for fixed intervals of time. Thus Scheduling of these resources constitutes a major part of resource management. An optimized scheduling of resources is required to maintain separation between users of the resources. In this paper, we discuss various resource scheduling strategies that have been and are being implemented in cloud computing environments. We also propose a comparison among the characteristics features of these resource scheduling algorithms.
Page(s) : 1419-1427
ISSN : 0975-4024
Source : Vol. 5, No.2