Age of Local Information for Fusion Freshness in Internet of Things
Age of Local Information for Fusion Freshness in Internet of Things
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DOI：
10.1109/iccc57788.2023.10233592
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发表时间：
2023-08
期刊：
影响因子：
--
通讯作者：
Taige Chang;Xianghui Cao;Y. Cheng
中科院分区：
文献类型：
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作者：
Taige Chang;Xianghui Cao;Y. Cheng
近年来，物联网（IoT）的应用已被广泛探索，在这些应用程序中，基于概率理论或人工智能（AI）的信息融合起着基本作用。考虑收集冗余数据的物联网节点的调度，以确保融合信息的新鲜度（AOI）在单源更新系统中，它几乎不适用于本文中的多源系统设置。融合中使用的物联网最小化AOI的到达率更高。例如Whittle的指数政策或AOI贪婪政策。
In recent years, the applications of Internet of Things (IoT) have been extensively explored. Among these applications, information fusion based on probability theories or Artificial Intelligence (AI) plays a foundational role. However, to the best of our knowledge, few works consider the scheduling of the IoT nodes that collect redundant data to promise the freshness of the fused information. Age of Information (AoI) is a metric that characterizes the obsolescence of information. Although AoI works well in single-source updating systems, it is hardly applicable to a multi-source system setting such as IoT. In this paper, we propose a new metric called Age of Local Information (AoLI) to illustrate the obsolescence of data collected by each node of IoT used in fusion. We first simulate AoLI in an FCFS queue and show that the optimal arrival rate that minimizes the mean AoI does not necessarily result in a quicker information fusion. Instead, the arrival rate that minimizes the maximal AoI performs better. We then propose a scheduling policy called the Fusion Greedy policy to schedule the IoT nodes in a discrete manner under an FCFS queue of length 1. Through simulation, we demonstrate that the proposed policy outperforms traditional policies such as Whittle’s index policy or the AoI Greedy policy.