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Can Decentralized Status Update Achieve Universally Near-Optimal Age-of-Information in Wireless Multiaccess Channels?

机译:分散的状态更新可以在无线多曲线频道中普遍接近最佳信息时代吗?

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In an Internet-of-Things system where status data are collected from sensors and actuators for time-critical applications, the freshness of data is vital and can be quantified by the recently proposed age-of-information (AoI) metric. In this paper, we first consider a general scenario where multiple terminals share a common channel to transmit or receive randomly generated status packets. The optimal scheduling problem to minimize AoI is formulated as a restless multi-armed bandit problem. To solve the problem efficiently, we derive the Whittle's index in closed-form and establish the indexability thereof. Compared with existing work, we extend the index policy for AoI optimization to incorporate stochastic packet arrivals and optimal packet management (buffering the latest packet). Inspired by the index policy which has near-optimal performance but is centralized by nature, a decentralized status update scheme, i.e., the index-prioritized random access policy (IPRA), is further proposed, achieving universally near-optimal AoI performance and outperforming state-of-the-arts in the literature.
机译:在用于时间关键应用的传感器和执行器中收集状态数据的情况下,数据的新鲜度至关重要,可以通过最近提出的信息年龄(AOI)度量来量化。在本文中,我们首先考虑一个通用场景,其中多个终端共享公共信道来发送或接收随机生成的状态分组。最大限度地调度问题最小化AOI被制定为焦躁的多武装强盗问题。为了有效地解决问题,我们从闭合形式推导出鞭状的指数并建立其可分性。与现有工作相比,我们扩展了AOI优化的索引策略,以合并随机数据包到达和最佳数据包管理(缓冲最新数据包)。受到近乎最佳性能但是由大自然集中的索引政策的启发,进一步提出了分散的状态更新方案,即索引优先考虑的随机访问策略(IPRA),实现了普遍近乎最佳的AOI性能和优于优势状态 - 在文献中的艺术。

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