A multipath resource updating approach for distributed controllers in software-defined network

软件定义网络中一种分布式控制器间的多路径资源更新方法

Abstract

Finding effective ways to collect the usage of network resources in all kinds of applications to ensure a distributed control plane has become a key requirement to improve the controller’s decision making performance. This paper explores an efficient way in combining dynamic NetView sharing of distributed controllers with the behavior of intra-service resource announcements and processing requirements that occur in distributed controllers, and proposes a rapid multipathing distribution mechanism. Firstly, we establish a resource collecting model and prove that the prisoner’s dilemma problem exists in the distributed resource collecting process in the Software-defined Network (SDN). Secondly, we present a bypass path selection algorithm and a diffluence algorithm based on Q-learning to settle the above dilemma. At last, simulation results are given to prove that the proposed approach is competent to improve the resource collecting efficiency by the mechanism of self-adaptive path transmission ratio of our approach, which can ensure high utilization of the total network we set up.

摘要

创新点

在分布式 SDN 环境下, 针对各类应用有效地收集网络资源已成为改善控制器决策能力及其性能的关键因素。 论文通过研究分布式控制器收集到的资源请求如何结合快速路径分发机制在域间资源的通告, 更新生成共享资源的动态网络视图, 并能为控制器决策提供有益帮助的方法。 首先, 建立资源收集模型并证明收集过程中存在着囚徒困境问题。 然后, 提出了基于 Q 学习的旁路路径选择算法和分流资源传输算法。 最后, 仿真结果表明自适应路径传输机制能有效地改善分布式控制器的资源收集及决策效率, 并提高全网的资源利用率。

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Correspondence to Chunming Wu.

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Wu, X., Wu, C., Lin, C. et al. A multipath resource updating approach for distributed controllers in software-defined network. Sci. China Inf. Sci. 59, 92301 (2016). https://doi.org/10.1007/s11432-016-5574-0

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Keywords

  • multipath
  • Pareto optimal
  • Q-learning

关键词

  • 软件定义网络
  • 多路径
  • 帕累托最优
  • Q 学习
  • 网络视图