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IJERT-EMS

Reducing Scenarios For Cost Optimzation Of Resource Provisioning In Cloud Computing


Reducing Scenarios For Cost Optimzation Of Resource Provisioning In Cloud  Computing
Authors : Dr. V. Venkatesa Kumar, C. Kalpana
Publication Date: 29-05-2013

Authors

Author(s):  Dr. V. Venkatesa Kumar, C. Kalpana

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.2 - Issue 6 (June - 2013)

e-ISSN:   2278-0181

Abstract

The Cloud Computing provides the computing resources to the Cloud users as service via the Internet. A resource provisioning method is vital to provide Cloud users, a set of computing resources for processing the tasks and to store the data in Cloud Computing. The Cloud provider may provide two types of provisioning schemes for computing resources namely Advance reservation and On-Demand schemes to the Cloud users. A Multistage Stochastic Programming model which considers a set of scenarios (Price and Demand Uncertainty) is used for the Resource Provisioning for reservation schemes in Cloud Computing. The optimization under uncertainty deals with a huge set of scenarios for real time problems. A huge set of scenarios consideration leads to consumption of time and computational complexity. To address this problem, a Scenario Reduction Technique is applied to reduce the number of scenarios and provides a lesser set of Scenarios. This Reduction Technique finds out a subset of the primary scenario set and probabilities are assigned to the condensed set of the scenarios. The scenario tree generation algorithm consecutively decreases the number of nodes of the each scenario by altering the tree model and by wrapping the alike scenarios.

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