文献类型：期刊文献

英文题名：DFA-VMP: An efficient and secure virtual machine placement strategy under cloud environment

作者：Ding, Weichao[1];Gu, Chunhua[1];Luo, Fei[1];Chang, Yaohui[1];Rugwiro, Ulysse[1];Li, Xiaoke[1];Wen, Geng[2]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai, Peoples R China;[2]Shanghai Univ Elect Power, Sch Informat Sci & Engn, Shanghai, Peoples R China

年份：2018

卷号：11

期号：2

起止页码：318

外文期刊名：PEER-TO-PEER NETWORKING AND APPLICATIONS

收录：;EI(收录号：20164002873043);WOS:【SCI-EXPANDED(收录号:WOS:000425166900011)】；

基金：This work is supported by the National Natural Science Foundation of China (Grant NO. 61472139).

语种：英文

外文关键词：Cloud computing; Virtual machine secure placement; Side-channel attack; Energy consumption; Resource loss; Firefly algorithm

摘要：The problem of Virtual Machine (VM) placement is critical to the security and efficiency of the cloud infrastructure. Nowadays most research focuses on the influences caused by the deployed VM on the data center load, energy consumption, resource loss, etc. Few works consider the security and privacy issues of the tenant data on the VM. For instance, as the application of virtualization technology, the VM from different tenants may be placed on one physical host. Hence, attackers may steal secrets from other tenants by using the side-channel attack based on the shared physical resources, which will threat the data security of the tenants in the cloud computing. To address the above issues, this paper proposes an efficient and secure VM placement strategy. Firstly, we define the related security and efficiency indices in the cloud computing system. Then, we establish a multi-objective constraint optimization model for the VM placement considering the security and performance of the system, and find resolution towards this model based on the discrete firefly algorithm. The experimental results in OpenStack cloud platform indicates that the above strategy can effectively reduce the possibility of malicious tenants and targeted tenants on the same physical node, and reduce energy consumption and resource loss at the data center.