论文标题
SDN中的优先流入和路由:精确和启发式方法
Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches
论文作者
论文摘要
本文提出了一种新颖的入学和路由方案,该方案考虑了网络流的任意分配优先级。提出的方法利用集中式软件定义的网络(SDN)功能来实现。提供了确切的启发式方法,以解决所陈述的优先流入和路由(PFAR)问题。提供最佳解决方案的确切方法基于整数线性编程(ILP)。鉴于找到确切和最佳解决方案所需的可能长时间的运行时间,提出了一种启发式方法。这种方法基于遗传算法(气体)。为了有效估计所提出的方法的性能,已经开发了能够生成半随机网络拓扑和流量的模拟器。大型问题实例(上升50个网络节点和数千个网络流)的实验结果,表明:i)通常可以在几秒钟内找到最佳解决方案(甚至是毫秒),而ii)启发式方法在固定时间的近距离溶液中产生近距离的解决方案(约95 \%的最佳);这些实验结果证明了所提出的方法的相关性。
This paper proposes a novel admission and routing scheme which takes into account arbitrarily assigned priorities for network flows. The presented approach leverages the centralized Software Defined Networking (SDN) capabilities in order to do so. Exact and heuristic approaches to the stated Priority Flow Admission and Routing (PFAR) problem are provided. The exact approach which provides an optimal solution is based on Integer Linear Programming (ILP). Given the potentially long running time required to find an exact and optimal solution, a heuristic approach is proposed; this approach is based on Genetic Algorithms (GAs). In order to effectively estimate the performance of the proposed approaches, a simulator that is capable of generating semi-random network topologies and flows has been developed. Experimental results for large problem instances (up 50 network nodes and thousands of network flows), show that: i) an optimal solution can be often found in few seconds (even milliseconds), and ii) the heuristic approach yields close-to-optimal solutions (approximately 95\% of the optimal) in a fixed amount of time; these experimental results demonstrate the pertinence of the proposed approaches.