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Randomized Parallel Scheduling Algorithm for Input Queued Crossbar Switches

机译:输入排队交叉开关的随机并行调度算法

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A significant research effort has been devoted in recent years to the design of simple and efficient scheduling algorithms for input-queued packet switches. Among these algorithms, scheduling policies based on Maximum Weight Matching (MWM) were proved to achieve 100% throughput under any admissible traffic load. However, MWM is impractical for its high computational complexity O(N~3). In this paper, we propose a new approximate algorithm to MWM using local search technique. Notably we observe that: (a) Local search is well suitable for parallel computation, (b) Currently each line card of high performance router has at least one processor. Based on the two important observations, a randomized parallel scheduling algorithm is proposed. It is proved to be rate stable and simulation results show that the proposed algorithm outperforms other randomized approximations to MWM.
机译:近年来,已经进行了大量的研究工作来设计用于输入排队的分组交换机的简单而有效的调度算法。在这些算法中,基于最大权重匹配(MWM)的调度策略被证明可以在任何允许的流量负载下实现100%的吞吐量。但是,由于MWM计算复杂度为O(N〜3),因此不切实际。在本文中,我们提出了一种使用局部搜索技术的MWM近似算法。值得注意的是,我们注意到:(a)本地搜索非常适合并行计算;(b)当前,高性能路由器的每个线卡都至少具有一个处理器。基于两个重要发现,提出了一种随机并行调度算法。事实证明,该算法是速率稳定的,仿真结果表明该算法优于MWM的其他随机近似算法。

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