He Yuqiao, Chen Guozhi, Chen Yuchao, Wang Jintao, Song Jian
Beijing National Research Center for Information Science and Technology (BNRist), Beijing 100084, China.
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.
Entropy (Basel). 2023 Sep 14;25(9):1331. doi: 10.3390/e25091331.
This study considers a wireless network where multiple nodes transmit status updates to a base station (BS) through a shared bandwidth-limited channel. Considering the random arrival of status updates, we measure the data freshness with the age of synchronization (AoS) metric; specifically, we use the time elapsed since the latest synchronization as a metric. The objective of this study is to minimize the weighted sum of the average AoS of the entire network while meeting the minimum throughput requirement of each node. We consider both the central scheduling scenario and the distributed scheduling scenario. In the central scheduling scenario, we propose the optimal stationary randomized policy when the transmission feedback is unavailable and the max-weight policy when it is available. In the distributed scenario, we propose a distributed policy. The complexity of the three scheduling policies is significantly low. Numerical simulations show that the policies can satisfy the throughput constraint in the central controlling scenario and the AoS performance of the max-weight policy is close to the lower bound.
本研究考虑了一个无线网络，其中多个节点通过共享的带宽受限信道向基站（BS）传输状态更新。考虑到状态更新的随机到达，我们使用同步年龄（AoS）指标来衡量数据新鲜度；具体而言，我们将自最新同步以来经过的时间用作指标。本研究的目标是在满足每个节点的最小吞吐量要求的同时，最小化整个网络平均AoS的加权和。我们考虑了集中调度场景和分布式调度场景。在集中调度场景中，我们提出了传输反馈不可用时的最优平稳随机策略以及传输反馈可用时的最大权重策略。在分布式场景中，我们提出了一种分布式策略。这三种调度策略的复杂度都非常低。数值模拟表明，这些策略在集中控制场景中可以满足吞吐量约束，并且最大权重策略的AoS性能接近下限。
