An ACO for Energy-Efficient and Traffic-Aware Virtual Machine Placement in Cloud Computing

Impact Factor:10.267

DOI number:10.1016/j.swevo.2021.101012

Affiliation of Author(s):School of Computing and Artificial Intelligence, Southwest Jiaotong University

Journal:Swarm and Evolutionary Computation

Key Words:Ant colony optimization,Cloud computing,Evolutionary computation,Virtual machine placement

Abstract:This paper formulates a virtual machine placement (VMP) problem, where the total power consumption of physical machines (PMs) and switches and the total network bandwidth resource consumption among VMs are jointly minimized. To address the problem, we present an energy- and traffic-aware ant colony optimization (ETA-ACO) algorithm. Three novel schemes are introduced to enhance the performance of ETA-ACO, including an energy- and bandwidth-aware PM selection scheme, a traffic-based VM ordering scheme, and a direct information exchange scheme. The first scheme consists of two steps when selecting a PM to host a given VM. In the first step, PMs with lower power consumption are preserved. In the second step, the one with the lowest bandwidth resource consumption is chosen to host the VM. In the second scheme, ETA-ACO places VMs in descending order by their traffic demands. The third scheme constructs new solutions by spreading the components of the best solution over a group of constructed solutions. Simulation results demonstrate that the three novel schemes are effective in adapting ETA-ACO for the VMP problem. Besides, ETA-ACO outperforms a number of state-of-the-art heuristics and metaheuristics in terms of solution quality.

Co-author:Huanlai Xing*,Jing Zhu,Rong Qu,Penglin Dai,Shouxi Luo,Muhammad Azhar Iqbal

Document Code:10.1016/j.swevo.2021.101012

Volume:68

ISSN No.:2210-6502

Translation or Not:no

Date of Publication:2021-10-31

Included Journals:SCI