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Title: PLAN: Joint policy- and network-aware VM management for cloud data centers
Authors: Cui, Lin
Tso, Fung Po
Pezaros, Dimitrios P.
Jia, Weijia
Zhao, Wei
Keywords: Data centers
Policy
Virtual machine
Migration
Issue Date: 2016
Publisher: © IEEE
Citation: CUI, L. ... et al, 2016. PLAN: Joint policy- and network-aware VM management for cloud data centers. IEEE Transactions on Parallel and Distributed Systems, 28 (4), pp.1163-1175.
Abstract: Policies play an important role in network configuration and therefore in offering secure and high performance services especially over multi-tenant Cloud Data Center (DC) environments. At the same time, elastic resource provisioning through virtualization often disregards policy requirements, assuming that the policy implementation is handled by the underlying network infrastructure. This can result in policy violations, performance degradation and security vulnerabilities. In this paper, we define PLAN, a PoLicy-Aware and Network-aware VM management scheme to jointly consider DC communication cost reduction through Virtual Machine (VM) migration while meeting network policy requirements. We show that the problem is NP-hard and derive an efficient approximate algorithm to reduce communication cost while adhering to policy constraints. Through extensive evaluation, we show that PLAN can reduce topology-wide communication cost by 38 percent over diverse aggregate traffic and configuration policies.
Description: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor: This work is partially supported by Chinese National Research Fund (NSFC) Chinese National Research Fund (NSFC) Project No.: 61402200 and 61373125; NSFC Key Project No. 61532013; National China 973 Project No. 2015CB352401; Shanghai Scientific Innovation Act of STCSM No. 15JC1402400 and 985 Project of Shanghai Jiao Tong University with No. WF220103001; the Science and Technology Fund of Macau (FDCT) Projects AQ2 under Grant 061/2011/A3 and Grant 092/2014/A2; the University of Macau Projects under Grant MYRG112-FST12-ZW and Grant MYRG2015-00165-FST; US National Science Foundation under grant 0963979; the UK Engineering and Physical Sciences Research Council (EPSRC) grants EP/N033957/1, EP/L026015/1, EP/L005255/1, EP/P004407/1 and EP/P004024/1.
Version: Accepted for publication
DOI: 10.1109/TPDS.2016.2604811
URI: https://dspace.lboro.ac.uk/2134/34230
Publisher Link: https://doi.org/10.1109/TPDS.2016.2604811
ISSN: 1045-9219
Appears in Collections:Published Articles (Computer Science)

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