A self-adaptive differential evolution algorithm fortask scheduling in cloud computing

Task scheduling is the most importantrequirement in cloud computing, which plays a vital role inenhancing the quality of services and reducing powerconsumption and processing time. This paper presents a selfadaptivedifferential evolution (SADE) algorithm for schedulingtasks in cloud computing. The proposed method models taskscheduling as a multi-modal optimization problem with theobjectives of minimizing makespan and energy consumption.The experiments on scheduling benchmarks show thesuperiority of the proposed method in most test cases comparedwith the peer methods.

Keywords:

Cloud computing , task scheduling , resourcemanagement , self-adaptive differential evolution , makespan , energy consumption