An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers

Salami, H.O. and Bala, A. and Sait, S.M. and Ismail, I. (2021) An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers. Journal of Supercomputing, 77 (11). pp. 13330-13357. ISSN 09208542

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The advent of virtualization technology has created a huge potential application for cloud computing. In virtualization, a large hardware resource is often broken down into smaller virtual units. These small units are then provisioned to different clients. However, these services need to be provided in such a way that resources are properly utilized. To achieve this, many of the scheduling, allocation, and provisioning issues of data centers are formulated as optimization problems. The virtual machine placement problem (VMPP) is a typical provisioning problem of data centers. In VMPP, several virtual machine requests are to be hosted on physical machines such that a minimum number of physical machines are used. This work proposes a cuckoo search (CS) inspired algorithm for solving the VMPP. To improve the algorithm�s performance, new cost and perturbation functions are developed. The proposed method was tested on two well-known benchmark datasets. It outperformed the reordered grouping genetic algorithm, best-fit decreasing, first-fit decreasing, and an earlier CS method called multiCSA. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Item Type: Article
Additional Information: cited By 12
Uncontrolled Keywords: Energy efficiency; Genetic algorithms; Network security; Virtual machine; Virtualization, Algorithm for solving; Best fit decreasing; Cuckoo search algorithms; Grouping genetic algorithms; Optimization problems; Perturbation functions; Virtual machine placements; Virtualization technologies, Cloud computing
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:28
Last Modified: 10 Nov 2023 03:28
URI: https://khub.utp.edu.my/scholars/id/eprint/14340

Actions (login required)

View Item
View Item