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Load-Optimization in Reconfigurable Networks: Algorithms and Complexity of Flow Routing

机译:可重新配置网络中的负载优化:流量路由的算法和复杂性

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Emerging reconfigurable data centers introduce the unprecedented flexibility in how the physical layer can be programmed to adapt to current traffic demands. These reconfigurable topologies are commonly hybrid, consisting of static and reconfigurable links, enabled by e.g. an Optical Circuit Switch (OCS) connected to top-of-rack switches in Clos networks. Even though prior work has showcased the practical benefits of hybrid networks, several crucial performance aspects are not well understood.In this paper, we study the algorithmic problem of how to jointly optimize topology and routing in reconfigurable data centers with a known traffic matrix, in order to optimize a most fundamental metric, maximum link load. We chart the corresponding algorithmic landscape by investigating both un-/splittable flows and (non-)segregated routing policies. We moreover prove that the problem is not submodular for all these routing policies, even in multi-layer trees, where a topological complexity classification of the problem reveals that already trees of depth two are intractable.However, networks that can be abstracted by a single packet switch (e.g., nonblocking Fat-Tree topologies) can be optimized efficiently, and we present optimal polynomial-time algorithms accordingly. We complement our theoretical results with trace-driven simulation studies, where our algorithms can significantly improve the network load in comparison to the state of the art.
机译:新兴的可重构数据中心引入了无法编程物理层以适应当前业务需求的前所未有的灵活性。这些可重新配置的拓扑是通常的混合动力,由静态和可重新配置的链路组成,由例如,通过例如启用。连接到CLOR网络的顶部机架开关的光电路开关(OCS)。尽管事先工作展示了混合网络的实际效益,但几个关键的性能方面也不太了解。在本文中,我们研究了如何在可重新配置的数据中心中共同优化拓扑和路由的算法问题为了优化最基本的度量标准,最大的链路负载。我们通过调查Un-/可分离的流量和(非)隔离路由策略来描绘相应的算法横向。我们还证明,即使在多层树中,问题也不是子模具,即使在多层树中,问题的拓扑复杂性分类揭示了已有深度的树木是棘手的。但是,可以用单个抽象的网络可以有效地优化分组开关(例如,非阻塞脂肪树拓扑),并且我们相应地显示了最佳多项式算法。我们通过追踪仿真研究来补充我们的理论结果,其中我们的算法可以与现有技术相比,我们的算法可以显着提高网络负载。

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