面向多接入边缘计算的VNFM分布式部署方案

doi:10.19665/j.issn1001-2400.2021.04.003

Abstract

Abstract:

Aiming at achieving efficient virtual network function deployment under the Mobile edge computing (MEC) architecture,a virtual network function manager (VNFM) deployment method based on the immune optimization algorithm is proposed.First,a mixed integer programming model is used to build the mathematical model of VNFM deployment.Then,a deployment solution based on the immune optimization algorithm is given.Aiming at obtaining the optimal deployment solution towards the minimum communication cost,the algorithm comprehensively considers the antibody affinity and antigen affinity of chromosomes with respect to individual fitness in the population and the diversity characteristics of the immune system,respectively.Simulation results show that compared with the current deployment method,the individual evaluation mechanism of the proposed algorithm can more effectively evaluate the fitness and similarity of individuals in VNFM deployment problems.The proposed method can effectively prevent the algorithm from falling into the local optimum during the deployment process.The optimal solution improves the performance of the algorithm;it can speed up the algorithm’s convergence efficiency and simultaneously reduce the CPU time for algorithm execution.

Key words: multi-access edge computing, immune optimization algorithm, virtual network function manager deployment

CLC Number:

TP393

MA Yue,ZHANG Yumei. Method for distributed deployment of the virtual network function manager for MEC[J].Journal of Xidian University, 2021, 48(4): 20-26.

Figures/Tables 7

References 19

[1]	MACH P, BECVAR Z. Mobile Edge Computing:A Survey on Architecture and Computation Offloading[J]. IEEE Communications Surveys & Tutorials, 2017, 19(3):1628-1656.
[2]	SAHHAF S, TAVERNIER W, ROST M, et al. NetworkService Chaining with Optimized Network Function Embedding Supporting Service Decompositions[J]. Computer Networks, 2015, 93(3):492-505. doi: 10.1016/j.comnet.2015.09.035
[3]	PEI Jianing, HONG Peiling, PAN Miao, et al. Optimal VNF Placement via Deep Reinforcement Learning in SDN/NFV-Enabled Networks[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(2):263-278. doi: 10.1109/JSAC.49
[4]	WANG Shuangguang, ZHOU A, HSU C H, et al. Provision of Data-Intensive Services Through Energy-and QoS-Aware Virtual Machine Placement in National Cloud Data Centers[J]. IEEE Transactions on Emerging Topics in Computing, 2016, 4(2):290-300. doi: 10.1109/TETC.6245516
[5]	CARPIO F, DHAHRI S, JUKAN A. VNF Placement with Replication for Loac Balancing in NFV Networks[C]//Proceedings of the 2017 IEEE International Conference on Communications(ICC).Piscataway:IEEE, 2017:1-6.
[6]	史久根, 张径, 徐皓, 等. 一种面向运营成本优化的虚拟网络功能部署和路由分配策略[J]. 电子与信息学报, 2019, 41(4):973-979.
	SHI Jiugen, ZHANG Jing, XU Hao, et al. A Strategy for Virtual Network Function Deployment and Route Allocation for Operation Cost Optimization[J]. Journal of Electronics & Information Technology, 2019, 41(4):973-979.
[7]	WEN Z, CALA J, WATSON P, et al. Cost Effective,Reliable and Secure Workflow Deployment Over Federated Clouds[J]. IEEE Transactions on Services Computing, 2017, 10(6):929-941. doi: 10.1109/TSC.2016.2543719
[8]	TAJIKI M, SALSANO S, CHIARAVIGLIO L, et al. Joint Energy Efficient and QoS-Aware Path Allocation and VNF Placement for Service Function Chaining[J]. IEEE Transactions on Network and Service Management, 2019, 16(1):374-388. doi: 10.1109/TNSM.4275028
[9]	BENKACEM I, TALEB T, BAGAA M, et al. Optimal VNFs Placement in CDN Slicing over Multi-Cloud Environment[J]. IEEE Journal on Selected Areas in Communications, 2018, 36(3):616-627. doi: 10.1109/JSAC.2018.2815441
[10]	BARIM F, CHOWDHURY S R, AHMED R, et al. Orchestrating Virtualized Network Functions[J]. IEEE Transactions on Network and Service Management, 2016, 13(4):725-739. doi: 10.1109/TNSM.2016.2569020
[11]	LI Keqin. A Game Theoretic Approach to Computation Offloading Strategy Optimization for Non-cooperative Users in Mobile Edge Computing[J]. IEEE Transactions on Sustainable Computing, 2018:1-1.
[12]	KATSALIS K, PAPAIOANNOU T G, NIKAEIN N, et al. SLA-Driven VM Scheduling in Mobile Edge Computing[C]//Proceedings of the 2016 IEEE 9th International Conference on Cloud Computing(CLOUD).San Francisco:CA,USA, 2016:750-757.
[13]	LI Chunlin, TANG Jianhang, LUO Youlong. Distributed QoS-Aware Scheduling Optimization for Resource-intensive Mobile Application in Hybrid Cloud[J]. Cluster Computing, 2018, 21(2):1331-1348. doi: 10.1007/s10586-017-1171-2
[14]	YE Qiang, ZHUANG Weihua, LI Xu, et al. End-to-End Delay Modeling for Embedded VNF Chains in 5G Core Networks[J]. IEEE Internet of Things Journal, 2019, 6(1):692-704. doi: 10.1109/JIOT.2018.2853708
[15]	YALA L, FRANGOUDIS P A, LUCARELLI G, et al. Balancing Between Cost and Availability for CDNaaS Resource Placement[C]//Proceedings of the 2017 IEEE Global Communications Conference.Piscataway:IEEE, 2017:1-7.
[16]	LEIVADEAS A, KESIDIS G, IBNKAHLA M, et al. VNF Placement Optimization at the Edge and Cloud[J]. Future Internet, 2019, 11(3):69. doi: 10.3390/fi11030069
[17]	MUTICHIRO B, YANG H, KIM Y. Latency-Aware VNF Placement for IoT Applications in Edge Computing[C]//Proceedings of the 2018 IEEE Global Communications Conference.Piscataway:IEEE, 2019:71-72.
[18]	崔志华, 张春妹, 时振涛, 等. 基于蝙蝠算法的观测矩阵优化算法[J]. 控制与决策, 2018, 33(7):1341-1344.
	CUI Zhihua, ZHANG Chunmei, SHI Zhentao, et al. Measurement Matrix Optimization Algorithm with Bat Algorithm[J]. Control and Decision, 2018, 33(7):1341-1344.
[19]	崔志华, 张茂清, 常宇, 张江江, 等. 基于平均距离聚类的NSGA-II[J/OL].[2021-03-09]. .

Method for distributed deployment of the virtual network function manager for MEC

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