A Dynamic Energy-saving Deployment Algorithm for Virtual Data Centers

被引:3
|
作者
Han, Shujun [1 ,2 ]
Li, Jun [1 ]
Ma, Yuxiang [3 ,4 ]
Dong, Qian [1 ,2 ,5 ]
Wu, Di [6 ]
机构
[1] Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Henan Univ, Sch Comp & Informat Engn, Kaifeng 475004, Peoples R China
[4] Henan Univ, Henan Key Lab Big Data Anal & Proc, Kaifeng 475004, Peoples R China
[5] Foshan Univ, Sch Elect Informat Engn, Foshan 528000, Peoples R China
[6] Peoples Bank China, Chengdu Branch, Chengdu 610041, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
NETWORK; PLACEMENT; MODEL;
D O I
10.1109/SmartCloud.2019.00026
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Network Function Virtualization (NFV) is a rapidly evolving network technology in recent years. The purpose of NFV is to use virtualization technology to softwareize network functions, and dynamically deploy virtual network functions (VNFs) according to the usage status of network links and the service requirements of users. NFV can increase the flexibility of network services and the utilization of network resources. In the proposed paper, we analyze the user data of urban computing, and propose that the time and location of the user's use of the network service is subject to regular changes. Based on this judement, we propose a new energy-saving deployment method for virtual data centers (vDCs). In this paper, we formalize the placement problem of vDC into a multicommodity flow problem and address it as an integer linear programming (ILP). We design a centrality-based greedy algorithm and evaluate its effectiveness by comparing the proposed algorithm with the ILP optimal solution. The evaluation results show that the greedy algorithm proposed in this paper can obtain the approximate optimal solution of ILP, and the running time of the proposed algorithm is shorter than the ILP solution when the number of network nodes increases.
引用
收藏
页码:92 / 97
页数:6
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