A Study on Load Prediction Methods for Optimal Resource Allocation in the Cloud Environment
||International Journal of Computer & Organization Trends (IJCOT)||
|© 2017 by IJCOT Journal|
|Volume - 7 Issue - 4
|Year of Publication : 2017|
|Authors : S.Sridevi, Dr. Jeevaa Katiravan|
S.Sridevi, Dr. Jeevaa Katiravan "A Study on Load Prediction Methods for Optimal Resource Allocation in the Cloud Environment", International Journal of Computer & organization Trends (IJCOT), V7(4):32-36 Jul - Aug 2017, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract In the cloud environment, utilization of resources should be scaled-up and scaled-down according to the customer needs. Managing the scalability in the cloud is a critical issue. Scalability can be accomplished by dynamic resource allocation. This dynamic resource allocation based on demand is efficient only on the knowledge of load prediction. Improving the accuracy of load prediction is essential to achieve optimal job scheduling and load balancing for cloud computing. When the load prediction and server reliability is carried out simultaneously, an optimal resource allocation is possible. Various load prediction methods are discussed in this paper.
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load prediction, prediction accuracy, dynamic resource allocation.