TASK SCHEDULING OPTIMIZATION OF INDEPENDENT TASKS IN CLOUD COMPUTING USING ENHANCED GENETIC ALGORITHM

Parallel and distributed computing has been entered into the era of cloud computing which provides highly scalable computational power and remote location data storage with secure, fast and in cost effective way. So it has captured the attention of big IT giants for availing flexible, readily elastic and cost effective economical IT operations. Cloud computing environments provide dynamically manageable virtualized computing resources. The management of these resources is taking big account in cloud. So the scheduling has of vital importance in cloud computing. In this paper, we give an elaborate idea about Genetic Algorithm and its several variants proposed for task scheduling in cloud environment and idea of GA based scheduler is proposed in which population is produced by Enhanced Max Min by which makespan can be reduced and load of resources can be balanced.

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