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A Low-Complexity Congestion Control and Scheduling Algorithm for Multihop Wireless Networks With Order-Optimal Per-Flow Delay

机译:具有订单最优单次延迟的多跳无线网络的低复杂性拥塞控制和调度算法

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摘要

Quantifying the end-to-end delay performance in multihop wireless networks is a well-known challenging problem. In this paper, we propose a new joint congestion control and scheduling algorithm for multihop wireless networks with fixedroute flows operated under a general interference model with interference degree K. Our proposed algorithm not only achieves a provable throughput guarantee (which is close to at least 1=K of the system capacity region), but also leads to explicit upper bounds on the end-to-end delay of every flow. Our end-to-end delay- and throughput-bounds are in simple and closed forms, and they explicitly quantify the tradeoff between throughput and delay of every flow. Further, the per-flow end-to-end delay bound increases linearly with the number of hops that the flow passes through, which is order-optimal with respect to the number of hops. Unlike traditional solutions based on the backpressure algorithm, our proposed algorithm combines windowbased flow control with a new rate-based distributed scheduling algorithm. A key contribution of our work is to use a novel stochastic dominance approach to bound the corresponding perflow throughput and delay, which otherwise are often intractable in these types of systems. Our proposed algorithm is fully distributed and requires a low per-node complexity that does not increase with the network size. Hence, it can be easily implemented in practice.
机译:量化多跳无线网络中的端到端延迟性能是一个众所周知的具有挑战性问题。在本文中,我们提出了一种新的联合拥塞控制和调度控制和调度算法,用于多跳无线网络,通过干扰度K的一般干扰模型运行的固定机器流。我们所提出的算法不仅实现了可提供的吞吐量保证(接近至少1 =系统容量区域的k),但也导致每个流的端到端延迟的显式上限。我们的端到端延迟和吞吐量界是简单且封闭的形式,并且他们明确地量化了吞吐量与每个流程的延迟之间的权衡。此外,每流端端到端延迟绑定随着流动通过的跳数而线性增加,这是关于相对于跳数的顺序最佳。与基于背压算法的传统解决方案不同,我们所提出的算法将Window基于基于速率的分布式调度算法的流量控制相结合。我们的工作的关键贡献是使用一种新的随机优势方法来束缚相应的性能吞吐量和延迟,否则这些类型通常是棘手的这些类型的系统。我们所提出的算法完全分布,需要使用网络大小不会增加的每个节点复杂度。因此,可以在实践中容易地实现。

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