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

Efficient 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.

Automated summary

This article presents an autonomic resource allocation approach based on antlion optimization for energy efficient utilization of resources while satisfying QoS needs. The proposed approach uses resource utilization history for autonomous allocation and can operate in different modes depending on workload conditions. Performance analysis in CloudSim simulator demonstrates the effectiveness of the approach.