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A hybrid NSGA-II for solving multiobjective controller placement in SDN

机译:用于解决SDN中多目标控制器放置的混合NSGA-II

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Unlike traditional networks that both control and data planes are tightly coupled on the same boxes, SDN decouples control and data planes. At the moment, this architecture is facing various challenges such as reliability, resiliency, scalability, and availability that should be considered in its future designs. One of the most important issues to address these challenges is the problem of controller placement, i.e., the deployment of a desired number of controllers within a network so that some requirements, which may be conflicting, are satisfied. Therefore, based on the fact that various types of objectives should be taken into consideration, this problem can be regarded as a multi-objective combinatorial optimization problem (MOCO). Hence, a single optimal placement for these competing objectives could not be achieved and decision makers need to look for an appropriate trade-off among them. An exhaustive evaluation of all possible placements can be performed well for small and medium sized networks. However, considering realistic time and resource constraints, heuristic approaches are needed to adapt and implement for large scale or dynamic networks whose properties change over time. For this purpose, a heuristic algorithm called hybrid NSGA-II is introduced which yields faster computation times and needs much less memory to perform. The results carried out in Matlab 2013b on the internet2 topology showed the efficiency of the proposed method.
机译:与将控制平面和数据平面都紧密耦合在同一盒子上的传统网络不同,SDN使控制平面和数据平面分离。目前,该架构面临各种挑战,例如在未来的设计中应考虑的可靠性,弹性,可伸缩性和可用性。应对这些挑战的最重要的问题之一是控制器的放置问题,即在网络内部署所需数量的控制器,从而满足可能冲突的某些要求。因此,基于应考虑各种类型目标的事实,此问题可以视为多目标组合优化问题(MOCO)。因此,无法实现这些竞争目标的单一最佳布局,决策者需要在它们之间寻求适当的权衡。对于中小型网络,可以对所有可能的位置进行详尽的评估。但是,考虑到实际的时间和资源限制,需要使用启发式方法来适应和实现属性随时间变化的大型或动态网络。为此,引入了一种称为混合NSGA-II的启发式算法,该算法产生更快的计算时间,并且需要更少的内存来执行。在Matlab 2013b中对internet2拓扑进行的结果表明了该方法的有效性。

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