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个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:teaching
性别:男
毕业院校:重庆大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 计算机软件与理论
办公地点:开发区综合楼405
联系方式:Email: zkchen@dlut.edu.cn Moble:13478461921 微信:13478461921 QQ:1062258606
电子邮箱:zkchen@dlut.edu.cn
Novel Framework of Risk-Aware Virtual Network Embedding in Optical Data Center Networks
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论文类型:期刊论文
发表时间:2018-09-01
发表刊物:IEEE SYSTEMS JOURNAL
收录刊物:ESI高被引论文、SCIE
卷号:12
期号:3
页面范围:2473-2482
ISSN号:1932-8184
关键字:Optical data center network (ODCN); risk detection and isolation; virtual network embedding
摘要:The traffic between geographically distributed data centers (DCs) becomes bandwidth hungry. Since the optical interconnection has a high capacity, the optical data center network (ODCN)-where DCs are located at the edge of the optical backbone-emerges. By virtualization, the virtual networks- representing service requirements-are embedded onto the same part of the substrate ODCN. Each virtual network has virtual machine (VM) nodes interconnected by virtual links (VLs). Therefore, a virtual network embedding (VNE) operation includes two components: 1) the VM mapping for putting a VM into the server of an appropriate DC and 2) the VL mapping for establishing one substrate path to support inter-VM communications. In this paper, we focus on a risk-aware VNE framework because a blind VNE operation would result in severe information leakage among coresident VMs in the server. By evaluating VM threat and vulnerability, risky VMs are identified according to experimental results. To perform physical isolation between risky and security VMs, a risk-aware VNE heuristic algorithm is proposed. The simulation results show that our heuristic algorithm performs better than the benchmark in terms of maintaining ODCN security and earning rental revenue. There is also a good match between our algorithm solution and the problem bound.