Energy and Fault Aware Virtual Machine Allocation using Machine Learning for Cloud Infrastructure

Abstract

Cloud computing offers various services to customers on a pay-per-use notion. Power consumption is conducive to cloud providers and it is linear to number of requests generated by users in the data center. Power consumption and the load of the data center increase as the number of requests increases. Hence, requests need to be balanced with effective strategies to handle failures and optimize power consumption. This paper proposes a machine learning technique to reduce power consumption and improve execution time. It is observed that the proposed technique performs well compare to other algorithms in terms of power efficiency and execution time.