Research Area:  Cloud Computing
To facilitate mobile cloud computing, a cloud service provider must dynamically create and terminate a large number of virtual machines (VMs), causing fragmented resources that cannot be further utilized. To solve this problem proactively, most of the existing studies have been based on server consolidation, with the main objective of minimizing the number of active servers. Although this approach can minimize resource fragmentation at a particular time, it may be over aggressive at the price of too frequent VM migration and low system stability. To address this issue, we propose a novel provident resource defragmentation framework that is revenue-oriented with the goal to reduce unnecessary VM migration. Within the proposed framework, we formulate an optimization problem for resource defragmentation at a particular time epoch, with the consideration of the future impact of any VM migration. We then develop an efficient heuristic algorithm that can obtain near-optimal results. Extensive numerical results confirm that our framework can provide the highest profit and can significantly reduce the VM migration cost in practical scenarios.
Author(s) Name:  Weigang Hou; Rui Zhang; Wen Qi; Kejie Lu; Jianping Wang and Lei Guo
Journal name:   IEEE Transactions on Emerging Topics in Computing
Publisher name:  IEEE
Volume Information:  Volume: 6, Issue: 1, Jan.-March 2018,Page(s): 32 - 44
Paper Link:   https://ieeexplore.ieee.org/document/7265056