Minimizing Age-of-Information with Throughput Requirements in Multi-Path Network Communication

Qingyu Liu, Haibo Zeng, Minghua Chen
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引用次数: 17

Abstract

We consider the scenario where a sender periodically sends a batch of data to a receiver over a multi-hop network, possibly using multiple paths. Our objective is to minimize peak/average Age-of-Information (AoI) subject to throughput requirements. The consideration of batch generation and multi-path communication differentiates our AoI study from existing ones. We first show that our AoI minimization problems are NP-hard, but only in the weak sense, as we develop an optimal algorithm with a pseudo-polynomial time complexity. We then prove that minimizing AoI and minimizing maximum delay are "roughly" equivalent, in the sense that any optimal solution of the latter is an approximate solution of the former with bounded optimality loss. We leverage this understanding to design a general approximation framework for our problems. It can build upon any α-approximation algorithm of the maximum delay minimization problem, e.g., the algorithm in [13] with α = 1 + ε given any user-defined ε > 0, to construct an (α + c)-approximate solution for minimizing AoI. Here c is a constant depending on the throughput requirements. Simulations over various network topologies validate the effectiveness of our approach.
多路径网络通信中具有吞吐量要求的信息年龄最小化
我们考虑这样一个场景:发送方通过多跳网络周期性地向接收方发送一批数据,可能使用多条路径。我们的目标是根据吞吐量需求最小化峰值/平均信息年龄(AoI)。考虑了批量生成和多路径通信,使我们的AoI研究区别于现有的研究。我们首先表明我们的AoI最小化问题是np困难的,但只是在弱意义上,因为我们开发了一个具有伪多项式时间复杂度的最优算法。然后我们证明最小化AoI和最小化最大延迟是“大致”等价的,因为后者的任何最优解都是具有有界最优性损失的前者的近似解。我们利用这种理解来为我们的问题设计一个一般的近似框架。它可以建立在最大延迟最小化问题的任意α-近似算法的基础上,例如[13]中的算法,当给定任意用户定义的ε > 0时,当α = 1 + ε时,构造最小化AoI的(α + c)-近似解。这里c是一个常数,取决于吞吐量需求。在各种网络拓扑上的仿真验证了我们方法的有效性。
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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