A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing

Abstract

Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper proposes an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment. We have analyzed the performance of our approach using the CloudSim toolkit. The experimental results show that our approach has immense potential as it offers significant improvement in the aspects of response time and makespan, demonstrates high potential for the improvement in energy efficiency of the data center, and can effectively meet the service level agreement requested by the users.

A Proposed Approach for Efficient Energy Utilization in Cloud Data Center

“…Wanneng Shu et al [12] presented a new energy effective algorithm for green cloud computing in which the resources are allocated on the basis of immune clonal optimization method. The performance of the algorithm was analyzed on cloudsim tool kit.…”

Green Cloud Computing: A Literature Survey

“…In the following years, the amount of research in the field of algorithms for cloud resource optimization increased. Shu et al [39] proposed an algorithm for clonal selection in the cloud, based on time, cost, and energy consumption. Xu et al [56] realized a management cloud computing framework to minimize energy consumption.…”

Impact of Energy-Efficient and Eco-Friendly Green Computing

“…The green computing aspires to achieve the aim of designing a highly power efficient, secure, environment-friendly and best performance computing system [8]. Green Cloud computing is envisioned to achieve not only efficiency in managing the allocation and working of the several operational resources including infrastructure, but limited consumption of energy too so that the future of the computing technology is sustainable [9].…”

“…Wanneng Shu et al [8] presented an improvised algorithm known as clonal selection on the basis of duration, expenses and the model for calculating the energy consumed in the cloud environment using CloudSim. Also, the parameters like amount of energy consumed and make span in association with the resources to be provisioned are considered.…”