Abstract:The studied technologies which were based on centralized physical devices and targeted on benefit optimization could not be applied in the enterprise network.To solve this problem,a cost optimization strategy based on location constrain(EL-VNE) was proposed for virtual network embedding in the enterprise network.Firstly,the computing and bandwidth capabilities were unified to a single node by using the complex theory,which decreased embedding times.Secondly,the EL-VNE model was presented and composed by mathematical descriptions about energy consumption,resource consumption and location constrain,which was proved to be NP-completed.Finally,heuristic algorithms were designed to find the solution of EL-VNE and then the embedding scheme with energy optimization was obtained.Compared with algorithms such as EAD and GLC,EL-VNE saves energy consumption in the process of embedding and running,and has better performance.
丛鑫, 訾玲玲, 杨东旭. 位置限制的企业级虚拟网络映射能源优化策略[J]. 电子学报, 2019, 47(8): 1654-1660.
CONG Xin, ZI Ling-ling, YANG Dong-xu. A Strategy of Energy Optimization in Enterprise Networks with Location-Constraint. Acta Electronica Sinica, 2019, 47(8): 1654-1660.
[1] Gong X X,et al.Virtual network embedding for collaborative edge computing in optical-wireless networks[J].Journal of Lightwave Technology,2017,35(18):3980-3990.
[2] Ogino,et al.Virtual network embedding with multiple priority classes sharing substrate resources[J].Computer Networks,2017,11(2):52-66.
[3] Papagianni C,et al.On the optimal allocation of virtual resources in cloud computing networks[J].IEEE Transactions on Computers,2013,62(6):1060-1071.
[4] Hong H J,et al.Placing virtual machines to optimize cloud gaming experience[J].IEEE Transactions on Cloud Computing,2015,3(1):42-53.
[5] Fard S Y Z,et al.A dynamic VM consolidation technique for QoS and energy consumption in cloud environment[J].The Journal of Supercomputing,2017,73(10):4347-4368.
[6] Zhang S,et al.Virtual network embedding with opportunistic resource sharing[J].IEEE Transactions on Parallel and Distributed Systems,2014,25(3):816-827.
[7] 陈晓华,等.虚拟网络映射高效节能运输模型及算法[J].电子学报,2016,44(3):725-731. Chen X H,et al.Transportation model and algorithms for energy efficient virtual network embedding[J].Acta Electronica Sinica,2016,44(3):725-731.(in Chinese)
[8] Elijorde F,et al.Attaining reliability and energy efficiency in cloud data centers through workload profiling and SLA-aware VM assignment[J].International Journal of Soft Computing and Its Applications,2015,7(1):41-58.
[9] Zhang Z,et al.Energy-aware virtual network embedding[J].IEEE/ACM Transactions on Networking,2014,22(5):1607-1620.
[10] Sun G,et al.Exploring online virtual networks mapping with stochastic bandwidth demand in multi-datacenter[J].Photonic Network Communications,2012,23(2):109-122.
[11] Chowdhury M,et al.Vineyard:Virtual network embedding algorithms with coordinated node and link mapping[J].IEEE/ACM Transactions on Networking,2012,20(1):206-219.
[12] Zhao J,et al.Virtual topology mapping in elastic optical networks[A].2013 IEEE International Conference on Communications[C].Budapest,Hungary:IEEE,2013.3904-3908.
[13] Gong L,et al.Novel location-constrained virtual network embedding LC-VNE algorithms towards integrated node and link mapping[J].IEEE/ACM Transactions on Networking.2016,24(6):3648-3661.
[14] 张忠宝.高效用低电能开销的虚拟网络映射算法研究[D].北京:北京邮电大学,2013.37-42. Zhang Z B.Research on key technologies for virtual network embedding with high utility and low energy cost[D].Beijing:Beijing University of Posts and Telecommunications,2013.37-42.(in Chinese)
[15] M.R.Garey,et al.Computers and intractablity:A guide to the theory of NP-Completeness[D].San Francisco,CA,USA:Freeman.1990.210,problem ND17.
[16] Zegura E W,et al.How to model an internetwork[A].1996 International Conference on Computer Communications[C].San Francisco,USA:IEEE,1996.594-602.
[17] Zhang H,et al.Self-organized virtual small networking for energy saving and load balancing in cellular networks[A].2015 IEEE International Conference on Communication Workshop[C].London,UK:IEEE,2015.2874-2879.