An autonomic resource management system for energy efficient and quality of service aware resource scheduling in cloud environment

Abstract

SummaryEfficient utilization of resources is a challenging task in cloud computing due to heterogeneity of resources and fluctuating resource demands of multifarious applications. This article presents an autonomic resource allocation approach for energy efficient utilization of resources while satisfying QoS needs of the end‐users. The proposed approach is based on antlion optimization and makes use of resource utilization history for autonomic allocation and efficient use of resources. It can operate in one of the three different modes namely, energy‐saving, performance, and balanced mode depending on the projected workload of an application. The performance analysis of the proposed approach is carried out in CloudSim simulator under different workload conditions.