Age-of-Information Bandits with Heterogeneous Data Rates

Harsh Deshpande, Sucheta Ravikanti, Sharayu Moharir
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引用次数: 2

Abstract

We consider a system with a sensor tracking a time-varying quantity and sending updates to a monitoring station using one of $K$ different data-rates for each update. The probability of an attempted update is an unknown function of the data-rate of the update. The metric of interest is the Age-of-Information (AoI), defined as the time elapsed since the sensor made the measurement sent in the latest update received by the monitoring station. The algorithmic challenge is to determine which data-rate to use to minimize cumulative AoI over a finite time-horizon. We propose two policies and characterize their performance via analysis and simulations. One of the key takeaways is that taking the current AoI into account while determining which data-rate to use is key for good performance. In addition, we study the trade-off between AoI and throughput for the system considered.
异构数据速率的信息时代强盗
我们考虑一个系统,该系统的传感器跟踪时变量,并为每次更新使用$K$不同的数据速率之一向监测站发送更新。尝试更新的概率是更新数据速率的未知函数。感兴趣的度量是信息年龄(Age-of-Information, AoI),定义为从传感器在监控站接收到的最新更新中发送测量到现在所经过的时间。算法的挑战在于确定在有限的时间范围内使用哪种数据速率来最小化累积AoI。我们提出了两种策略,并通过分析和仿真对其性能进行了表征。一个关键的结论是,在确定使用哪种数据速率是获得良好性能的关键时,要考虑当前的AoI。此外,我们还研究了所考虑系统的AoI和吞吐量之间的权衡。
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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