Title: Cost and green aware workload migration on geo-distributed datacentres

Authors: Jiacheng Jiang; Yingbo Wu; De Xiang; Keqin Yu; Tianhui Wang

Addresses: School of Software Engineering, Chongqing University, Chongqing 401331, China ' School of Software Engineering, Chongqing University, Chongqing 401331, China ' School of Software Engineering, Chongqing University, Chongqing 401331, China ' School of Software Engineering, Chongqing University, Chongqing 401331, China ' School of Software Engineering, Chongqing University, Chongqing 401331, China

Abstract: With the development of the inter-datacentre (inter-DC) virtual machine migration technology, it is possible to reduce the cost of electricity and the environment by using the workload migration across the datacentre. This paper presents a solution - cost and green aware workload migration algorithm (CGWM) that utilising the difference of electricity prices, CO2 emissions and water consumption between different geographical locations to manage the workload. CGWM attempts to reduce electricity costs, carbon emissions and water consumption. When the three optimisation goals conflict, CGWM first to ensure the reduction of electricity cost, and then by adjusting the weight factor to make CGWM more biased to optimise the carbon dioxide or water consumption. Simulation results show CGWM can reduce electricity costs while controlling carbon dioxide emissions and water consumption.

Keywords: cloud computing; VM migration; geographical datacentres; green datacentres; carbon dioxide emissions; greedy algorithm.

DOI: 10.1504/IJITM.2019.099817

International Journal of Information Technology and Management, 2019 Vol.18 No.2/3, pp.213 - 226

Received: 07 Jul 2017
Accepted: 24 Oct 2017

Published online: 10 May 2019 *

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