Journal of Computer Applications ›› 2018, Vol. 38 ›› Issue (1): 207-211.DOI: 10.11772/j.issn.1001-9081.2017071681

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Controller deployment strategy based on delay optimization in software defined network

FAN Zifu, YAO Jie, YANG Xianhui   

  1. Institute for Application Technology of Next Generation Network, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2017-07-10 Revised:2017-09-04 Online:2018-01-10 Published:2018-01-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61701064), the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ1600424), the Doctor Research Startup Foundation of Chongqing University of Posts and Telecommunications (A2015-41), the Science Research Project of Chongqing University of Posts and Telecommunications for Young Scholars (A2015-62).

基于时延优化的软件定义网络控制层部署策略

樊自甫, 姚杰, 杨先辉   

  1. 重庆邮电大学 下一代网络应用技术研究所, 重庆 400065
  • 通讯作者: 姚杰
  • 作者简介:樊自甫(1977-),男,安徽舒城人,副教授,硕士,主要研究方向:下一代网络技术、通信运营管理;姚杰(1994-),男,湖北荆门人,硕士研究生,主要研究方向:下一代网络技术、软件定义网络;杨先辉(1990-),男,山东济宁人,硕士研究生,主要研究方向:下一代网络技术、软件定义网络。
  • 基金资助:
    国家自然科学基金资助项目(61701064);重庆市教委科学技术项目(KJ1600424);重庆邮电大学博士科研启动基金资助项目(A2015-41);重庆邮电大学青年科学基金资助项目(A2015-62)。

Abstract: Most of the controller deployment programs in Software Defined Network (SDN) are focused on the propagation delay under normal network state, ignoring link fault state on the delay. To solve these problems, a controller deployment scheme based on delay optimization was proposed. Firstly, based on the worst delay minimization problem under normal network states and multiple single-link fault states, the network state delay was used as the new delay optimization goal to establish a controller deployment model. Secondly, two heuristic deployment algorithms were proposed to solve the above model:Controller Placement Algorithm based on Greedy Algorithm (GA-CPA) and Controller Placement Algorithm based on Particle Swarm Optimization (PSO-CPA). Finally, in order to measure the performance of the solutions, some real network topologies and data were chosen to verify the validity. The simulation results show that GA-CPA and PSO-CPA algorithms can reduce the network state delay in different degrees, thus ensuring that the worst delay in most network states is maintained at a lower range.

Key words: Software Defined Network (SDN), controller deployment, delay, link failure, Particle Swarm Optimization (PSO) algorithm, greedy algorithm

摘要: 当前大多数软件定义网络(SDN)中控制器的部署方案均重点考虑正常网络状态下传播时延对性能的影响,而忽略了链路故障状态下对时延的影响,针对此问题,提出了一种基于时延优化的控制层部署方案。首先,在综合考虑网络正常运行以及单链路故障等多种网络状态下的最坏情况时延最小化问题的基础上,以网络状态时延作为新的时延优化目标并建立了相应的数学模型。其次,提出了解决上述模型的两种启发式部署算法:基于贪婪算法的控制层部署算法(GA-CPA)和基于粒子群优化(PSO)算法的控制层部署算法(PSO-CPA)。最后,选取了真实网络拓扑及数据进行验证。仿真结果表明,GA-CPA和PSO-CPA两种部署算法均能在不同程度上降低网络状态时延,从而保证了大部分网络状态下的最坏情况时延维持在较低范围。

关键词: 软件定义网络, 控制层部署, 时延, 链路故障, 粒子群优化算法, 贪婪算法

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