夏秋粉

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:女

毕业院校:澳大利亚国立大学

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

办公地点:大连理工大学开发区校区信息楼

联系方式:0411-62274368

电子邮箱:qiufenxia@dlut.edu.cn

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Throughput optimization for admitting NFV-enabled requests in cloud networks

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论文类型:期刊论文

第一作者:Xu, Zichuan

通讯作者:Xia, QF (reprint author), Dalian Univ Technol, Dalian, Peoples R China.

合写作者:Liang, Weifa,Galis, Alex,Ma, Yu,Xia, Qiufen,Xu, Wenzheng

发表时间:2018-10-09

发表刊物:COMPUTER NETWORKS

收录刊物:SCIE

卷号:143

页面范围:15-29

ISSN号:1389-1286

关键字:Throughput maximization; Cost minimization; Approximation algorithms; Online algorithms; Network function virtualization; Algorithm analysis

摘要:Network softwarization is emerging as a techno-economic transformation trend that impacts the way that network service providers deliver their network services significantly. As a key ingredient of such a trend, network function virtualization (NFV) is shown to enable elastic and inexpensive network services for next-generation networks, through deploying flexible virtualized network functions (VNFs) running in virtual computing platforms. Different VNFs can be chained together to form different service chains for different network services, to meet various user data routing demands. From the service provider point of view, such services are usually implemented by VNF instances in a cloudlet network consisting of a set of data centers and switches. In this paper we consider provisioning network services in a cloud network for implementing VNF instances of service chains, where the VNF instances in each data center are partitioned into K types with each hosting one type of service chain. We investigate the throughput maximization problem with the aim to admit as many user requests as possible while minimizing the implementation cost of the requests, assuming that limited numbers of instances of each service chain have been instantiated in data centers. We first show the problem is NP-Complete, and propose an optimal algorithm for a special case of the problem when all requests have identical packet rates; otherwise, we devise two approximation algorithms with approximation ratios, depending on whether the packet traffic of each request is splittable. If arrivals of future requests are not known in advance, we study the online throughput maximization problem by proposing an online algorithm with a competitive ratio. We finally conduct experiments to evaluate the performance of the proposed algorithms by simulations. Simulation results show that the performance of the proposed algorithms are promising. (C) 2018 Elsevier B.V. All rights reserved.