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Wireless Communications and Mobile Computing
Volume 2017, Article ID 6741972, 11 pages
https://doi.org/10.1155/2017/6741972
Research Article

MeReg: Managing Energy-SLA Tradeoff for Green Mobile Cloud Computing

School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

Correspondence should be addressed to Rahul Yadav; nc.ude.tih.uts@luhar and Weizhe Zhang; nc.ude.tih@gnahzzw

Received 1 August 2017; Revised 13 October 2017; Accepted 1 November 2017; Published 17 December 2017

Academic Editor: Javier Bajo

Copyright © 2017 Rahul Yadav and Weizhe Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Mobile cloud computing (MCC) provides various cloud computing services to mobile users. The rapid growth of MCC users requires large-scale MCC data centers to provide them with data processing and storage services. The growth of these data centers directly impacts electrical energy consumption, which affects businesses as well as the environment through carbon dioxide (CO2) emissions. Moreover, large amount of energy is wasted to maintain the servers running during low workload. To reduce the energy consumption of mobile cloud data centers, energy-aware host overload detection algorithm and virtual machines (VMs) selection algorithms for VM consolidation are required during detected host underload and overload. After allocating resources to all VMs, underloaded hosts are required to assume energy-saving mode in order to minimize power consumption. To address this issue, we proposed an adaptive heuristics energy-aware algorithm, which creates an upper CPU utilization threshold using recent CPU utilization history to detect overloaded hosts and dynamic VM selection algorithms to consolidate the VMs from overloaded or underloaded host. The goal is to minimize total energy consumption and maximize Quality of Service, including the reduction of service level agreement (SLA) violations. CloudSim simulator is used to validate the algorithm and simulations are conducted on real workload traces in 10 different days, as provided by PlanetLab.