Cost and Power Consumption Joint Optimization Based Virtual Network Embedding Algorithm for Software-Defined Networking

被引：0
|
作者：
Chai R. [1 ]
Xie D.-S. [1 ]
Chen Q.-B. [1 ]
机构：
[1] School of Communication and Information Engineering, Chongqing University of Post and Telecommunications, Chongqing
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2021年 / 49卷 / 08期
关键词：
Heuristic algorithm; Joint optimization; Software-defined networking; Virtual network embedding;
D O I：
10.12263/DZXB.20190688
中图分类号：
学科分类号：
摘要：
For the network scenario where multiple virtual network requests (VNRs) arrive dynamically, a cost and power consumption joint optimization based virtual network embedding (VNE) algorithm was proposed for software-defined networking (SDN). Based on the evaluation of the cost and power consumption required for embedding virtual nodes and links, the cost function of VNE was formulated. Under the constraints of resource requirements, the VNE problem was formulated as cost function minimization problem. A time window-based batch embedding strategy was proposed to dynamically process online VNRs. The VNR in certain time window was transformed into virtual node embedding subproblem and virtual link embedding subproblem, and the corresponding heuristic algorithms were proposed, respectively. Simulation results showed that the proposed algorithm reduced the cost and power consumption of VNRs, and improved the acceptance ratio of VNRs. © 2021, Chinese Institute of Electronics. All right reserved.
引用
收藏
页码：1615 / 1624
页数：9
相关论文
共 24 条
  • [1] Kreutz D, Ramos F M V, Verissimo P E, Et al., Software-defined networking: a comprehensive survey, Proceedings of the IEEE, 103, 1, pp. 17-76, (2015)
  • [2] Khan A, Zugenmaier A, Jurca D, Et al., Network virtualization: a hypervisor for the Internet, IEEE Communications Magazine, 50, 1, pp. 136-143, (2012)
  • [3] Chowdhury M, Rahman M R, Boutaba R., ViNEYard: Virtual network embedding algorithms with coordinated node and link mapping, IEEE/ACM Transactions on Networking, 20, 1, pp. 206-219, (2012)
  • [4] Fischer A, Botero J F, Beck M T, Et al., Virtual network embedding: a survey, IEEE Communications Surveys and Tutorials, 15, 4, pp. 1888-1906, (2013)
  • [5] Liu H L, Hu H, Chen Y, Et al., Joint power consumption and load balancing algorithm for virtual optical network embedding, Acta Electronica Sinica, 47, 12, pp. 2488-2494, (2019)
  • [6] Zhang P Y, Yao H P, Liu Y J., Virtual network embedding based on computing, network, and storage resource constraints, IEEE Internet of Things Journal, 5, 5, pp. 3298-3304, (2018)
  • [7] Liu X, Zhang Z B, Li X M, Et al., Optimal virtual network embedding based on artificial bee colony, EURASIP Journal on Wireless Communications and Networking, 2016, 1, pp. 1-9, (2016)
  • [8] Yan Z X, Ge J G, Wu Y L, Et al., Automatic virtual network embedding: a deep reinforcement learning approach with graph convolutional networks, IEEE Journal on Selected Areas in Communications, 38, 6, pp. 1040-1057, (2020)
  • [9] Beck M T, Fischer A, Botero J F, Et al., Distributed and scalable embedding of virtual networks, Journal of Network and Computer Applications, 56, pp. 124-136, (2015)
  • [10] Zhang P Y., Incorporating energy and load balance into virtual network embedding process, Computer Communication, 129, pp. 80-88, (2018)
123