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Bandwidth Scheduling with Flexible Multi-paths in High-Performance Networks

机译:高性能网络中具有灵活多径的带宽调度

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Modern data-intensive applications require the transfer of big data over high-performance networks (HPNs) through bandwidth reservation for various purposes such as data storage and analysis. The key performance metrics for bandwidth scheduling include the utilization of network resources and the satisfaction of user requests. In this paper, for a given batch of Deadline-Constrained Bandwidth Reservation Requests (DCBRRs), we attempt to maximize the number of satisfied requests with flexible scheduling options over link-disjoint paths in an HPN while achieving the best average Earliest Completion Time (ECT) or Shortest Duration (SD) of scheduled requests. We further consider this problem from two bandwidth-oriented principles: (i) Minimum Bandwidth Principle (MINBP), and (ii) Maximum Bandwidth Principle (MAXBP). We show that both of these problem variants are NP-complete, and propose two heuristic algorithms with polynomial-time complexity for each. We conduct bandwidth scheduling experiments on both small-and large-scale DCBRRs in a real-life HPN topology for performance comparison. Extensive results show the superiority of the proposed algorithms over existing ones in comparison.
机译:现代数据密集型应用程序需要通过带宽预留在高性能网络(HPN)上传输大数据,以实现各种目的,例如数据存储和分析。带宽调度的关键性能指标包括网络资源的利用率和用户请求的满意度。在本文中,对于给定的最后期限约束带宽预留请求(DCBRR),我们尝试通过HPN中链路不相交路径上的灵活调度选项来最大化满足的请求数量,同时实现最佳的平均最早完成时间(ECT) )或预定请求的最短持续时间(SD)。我们从两个面向带宽的原则中进一步考虑了这个问题:(i)最小带宽原则(MINBP)和(ii)最大带宽原则(MAXBP)。我们证明这两个问题变体都是NP完全的,并提出了两个启发式算法,每个算法具有多项式时间复杂度。我们在现实的HPN拓扑中对小型和大型DCBRR进行带宽调度实验,以进行性能比较。大量结果表明,与现有算法相比,所提出算法的优越性。

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