提高动态背压算法的延迟性能
Enhancing the Delay Performance of Dynamic Backpressure Algorithms
摘要：
对于一般的多跳路由网络，时延最优控制一直是一个突出的问题。动态背压（BP）算法优雅地实现了吞吐量最优，但一般不会产生良好的延迟性能。在本文中，我们得到了一个渐近延迟的最优控制策略，它类似于BP算法的基础上的反压力计算的资源分配和路由，但不同的反压力计算的形式从BP算法。该差异表明BP算法的延迟性能不令人满意的可能原因，即，BP控制的短视本质。出于这种新的连接，我们引入了一类新的增强背压为基础的算法，将一个一般的依赖于偏置函数到传统的BP算法的背压项，以提高延迟性能。这些增强的算法利用队列状态信息超过一跳。我们证明了吞吐量的最优性和特点的效用延迟权衡的增强算法。我们进一步专注于这一类中的两个特定的分布式算法，这已被证明提高了延迟性能以及可接受的实现复杂度。
英文摘要：
For general multi-hop queueing networks, delay optimal network control has unfortunately been an outstanding problem. The dynamic backpressure (BP) algorithm elegantly achieves throughput optimality, but does not yield good delay performance in general. In this paper, we obtain an asymptotically delay optimal control policy, which resembles the BP algorithm in basing resource allocation and routing on a backpressure calculation, but differs from the BP algorithm in the form of the backpressure calculation employed. The difference suggests a possible reason for the unsatisfactory delay performance of the BP algorithm, i.e., the myopic nature of the BP control. Motivated by this new connection, we introduce a new class of enhanced backpressure-based algorithms which incorporate a general queue-dependent bias function into the backpressure term of the traditional BP algorithm to improve delay performance. These enhanced algorithms exploit queue state information beyond one hop. We prove the throughput optimality and characterize the utility-delay tradeoff of the enhanced algorithms. We further focus on two specific distributed algorithms within this class, which have demonstrably improved delay performance as well as acceptable implementation complexity.
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