A Profit Maximization Servies Function Chain Orchestration Algorithm

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A Profit Maximization Servies Function Chain Orchestration Algorithm

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[1]HUANG Hua,JIANG Jun,YANG Yongkang,et al.A Profit Maximization Servies Function Chain Orchestration Algorithm[J].Journal of Zhengzhou University (Engineering Science),2022,43(06):22-29.[doi:10.13705/j.issn.1671-6833.2022.03.017]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 43卷 Number of periods: 2022 06 Page number: 22-29 Column: Public date: 2022-09-02

Title:: A Profit Maximization Servies Function Chain Orchestration Algorithm

Author(s):: HUANG Hua¹; 2; JIANG Jun³; YANG Yongkang²; HE Defeng¹; CAO Bin⁴; 1.College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China;
2.Eastern Communications Co., Ltd.， Hangzhou 310053, China;
3.College of Information Science and Electrical Engineering, Zhejiang Shuren University, Hangzhou 310053, China;
4.College of Computer Science and Technology, College of Software, Zhejiang University of Technology, Hangzhou 310023, China

Keywords:: network function virtualization; service function chain; flexible allocation; combinatorial optimization

CLC:: TP393

DOI:: 10.13705/j.issn.1671-6833.2022.03.017

Abstract:: In this study, the service function chain (SFC) orchestration problem in data centers was investigated. The relationship between request arrival rate, computing resources and processing delay were analized. A flexible resource allocation optimization model aiming at maximize deployment benefits was proposed. Moreover, a heuristic method is developed to solve the problem in two stages. Firstly, the resource usage for SFC was optimized based on flexible resource allocation considering service delay. Secondly, for the virtual network function deployment and link mapping, the top-down and bottom-up search strategies based on worst-fit strategy were alternately adopted to improve the deployment efficiency and reduce the SFC delay. Finally, simulation with 4 and 6 pods in data center was designed to verify the performance of our heuristic algorithm. Experimental results demonstrated that, compared with existing methods, the development profit, success rate and resource utilization were improved in our algorithm.

References:: [1] GHAZNAVI M, SHAHRIAR N, KAMALI S, et al. Distributed service function chaining [ J] . IEEE journal on selected areas in communications, 2017, 35 (11) : 2479-2489.
[2] HAN B, VIJAY G, JI L S, et al. Network function virtualization: challenges and opportunities for innovations [J]. IEEE communications magazine, 2015, 53 ( 2): 90-97.

[3] MIJUMBI R, SERRAT J, GORRICHO J L, et al. Management and orchestration challenges in network functions virtualization [ J ] . IEEE communications magazine, 2016, 54(1) : 98-105.
[4] AGARWAL S, MALANDRINO F, CHIASSERINI C F, et al. VNF placement and resource allocation for the support of vertical services in 5G networks [ J ] . IEEE / ACM transactions on networking, 2019, 27 (1) : 433-446.
[5] GIL-HERRERA J, BOTERO J F. Resource allocation in NFV: a comprehensive survey [ J] . IEEE transactions on network and service management, 2016, 13 (3) : 518-532.
[6] BARI 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.

[7] LI D F, HONG P L, XUE K P, et al. Virtual network function placement considering resource optimization and SFC requests in cloud datacenter[ J] . IEEE transactions on parallel and distributed systems, 2018, 29 (7) : 1664-1677.

[8] LI Y, XUAN PHAN L T, LOO B T. Network functions virtualization with soft real-time guarantees [ C] ∥The 35th Annual IEEE International Conference on Computer Communications. Piscataway:IEEE, 2016: 1-9.

[9] QIAO W X, LIU Y C, LU Y, et al. A novel approach for service function chain embedding in cloud datacenter networks [ J ] . IEEE communications letters, 2021, 25(4) : 1134-1138.

[10] YU H F, CHEN Z R, SUN G, et al. Profit maximization of online service function chain orchestration in an inter-datacenter elastic optical network [ J ] . IEEE transactions on network and service management, 2021, 18(1) : 973-985.

[11] THAI M T, LIN Y D, LAI Y C. A joint network and server load balancing algorithm for chaining virtualized network functions[C]∥2016 IEEE International Conference on Communications. Piscataway:IEEE, 2016: 1-6.

[12] LIU Y C, LU H, LI X, et al. Dynamic service function chain orchestration for NFV / MEC-enabled IoT networks: a deep reinforcement learning approach[ J] . IEEE internet of things journal, 2021, 8 ( 9 ) : 7450-7465.

[13] ALLEG A, AHMED T, MOSBAH M, et al. Delayaware VNF placement and chaining based on a flexible resource allocation approach [ C]∥2017 13th International Conference on Network and Service Management (CNSM) . Piscataway:IEEE, 2017: 1-7.

[14] ROCHER-GONZALEZ J, ESCUDERO-SAHUQUILLO J, GARCÍA P J, et al. Towards an efficient combination of adaptive routing and queuing schemes in fat-tree topologies[ J] . Journal of parallel and distributed computing, 2021, 147: 46-63.

[15] 陈振荣. 数据中心网络中服务功能链的部署算法研究[D] . 成都: 电子科技大学, 2020.

CHEN Z R. Research on the algorithms for deploying service function chains in data center network [ D] . Chengdu: University of Electronic Science and Technology of China, 2020.

[16] 陈宝林. 最优化理论与算法[ M] . 2 版. 北京: 清华大学出版社, 2005. CHEN B L. Optimal theory and algorithm [ M] . 2nd ed. Beijing: Tsinghua University Press, 2005.

[17] 赵瑞安,吴方. 非线性最优化理论和方法[ M] . 杭州: 浙江科学技术出版社, 1992.

ZHAO R A,WU F. Theory and methods for nonlinear optimization [ M ] . Hangzhou: Zhejiang Science & Technology Press, 1992.

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Last Update: 2022-10-03