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A New Backpressure Algorithm for Joint Rate Control and Routing With Vanishing Utility Optimality Gaps and Finite Queue Lengths

机译:效用最优间隙消失且队列长度有限的联合速率控制和路由选择的新反压算法

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The backpressure algorithm has been widely used as a distributed solution to the problem of joint rate control and routing in multi-hop data networks. By controlling an algorithm parameter, the backpressure algorithm can achieve an arbitrarily small utility optimality gap. However, this in turn brings in a large queue length at each node and hence causes large network delay. This phenomenon is known as the fundamental utility-delay tradeoff. The best known utility-delay tradeoff for general networks is [O(∈), O(1/∈)] and is attained by a backpressure algorithm based on a drift-plus-penalty technique. This may suggest that to achieve an arbitrarily small utility optimality gap, backpressure-based algorithms must incur arbitrarily large queue lengths. However, this paper proposes a new backpressure algorithm that has a vanishing utility optimality gap, so utility converges to exact optimality as the algorithm keeps running, while queue lengths are bounded throughout by a finite constant. The technique uses backpressure and drift concepts with a new method for convex programming.
机译:背压算法已被广泛用作分布式解决方案,以解决多跳数据网络中的联合速率控制和路由问题。通过控制算法参数,背压算法可以实现任意小的效用最优间隙。但是,这又在每个节点上引入了较大的队列长度,因此导致了较大的网络延迟。这种现象被称为基本效用延迟权衡。通用网络中最广为人知的效用-延迟折衷是[O(ε),O(1 /ε)],它是通过基于漂移加罚技术的反压算法获得的。这可能表明,要实现任意小的效用最优间隔,基于反压的算法必须导致任意大的队列长度。但是,本文提出了一种新的反压算法,该算法具有消失的效用最优间隙,因此当算法持续运行时,效用收敛到精确的最优状态,而队列长度始终以有限常数为界。该技术使用反压和漂移概念以及用于凸编程的新方法。

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