A scalable scheduling algorithm to avoid conflicts in switch-memory-switch routers

Yang Xu, Beibei Wu, Wenjie Li, B. Liu
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引用次数: 5

Abstract

Although output queued (OQ) switches are prominent for their high performance, they are not easy to implement due to the high speedup requirement. Using a special scheduling algorithm in the first stage switch, a more scalable switch-memory-switch (SMS) architecture can emulate an OQ switch, where cells must be transferred from the inputs to the shared memories per time slot without arrival and departure conflicts. Although scheduling algorithm achieves good performance, the time complexity for constructing the bipartite graph is too high to be used in practice. In this paper, we propose a new iterative random round-Robin matching (iRRM) algorithm together with its constrained version CiRRM, where no bipartite graph is required to be constructed in advance to solve the departure conflict, and thus high computation overhead is avoided. In our algorithms, both the arrival and the departure conflicts are melted in the iterations. Each iterations consist of two steps: request step and grant step, where randomness and more easily implemented round-robin principle are used respectively. Through theoretical analysis, we obtain that with M=2/spl phi/(N-1) shared memories, where N is the port number and /spl phi/ is a constant larger than (2N-1)/(2N-2), iRRM/CiRRM can complete a matching within O(logM) iterations with high probability in M and the time complexity of CiRRM is only O(log/sup 2/M/loglogM), which is much lower than prior algorithms.
一种避免交换-内存-交换路由器冲突的可伸缩调度算法
尽管输出队列(OQ)开关以其高性能而闻名,但由于高加速要求,它们不容易实现。在第一阶段交换中使用一种特殊的调度算法,一种更具可扩展性的交换-内存交换(SMS)架构可以模拟OQ交换,其中每个时隙必须将单元从输入传输到共享存储器,而不存在到达和离开冲突。调度算法虽然取得了较好的性能,但其构造二部图的时间复杂度太高,难以应用于实际。本文提出了一种新的迭代随机轮循匹配算法(iRRM)及其约束版本CiRRM,该算法不需要预先构造二部图来解决出发冲突,从而避免了较高的计算开销。在我们的算法中,到达冲突和离开冲突在迭代中被融合。每次迭代包括两个步骤:请求步骤和授予步骤,其中分别使用随机性和更容易实现的轮询原则。通过理论分析,我们得到当M=2/spl phi/(N-1)个共享内存,其中N为端口号,/spl phi/为大于(2N-1)/(2N-2)的常数时,iRRM/CiRRM可以在M内高概率地在O(logM)次迭代内完成匹配,CiRRM的时间复杂度仅为O(log/sup 2/M/loglogM),大大低于之前的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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