论文标题
通过继电器最小化信息时代的最佳调度策略
Optimal Scheduling Policy for Minimizing Age of Information with a Relay
论文作者
论文摘要
我们考虑了IoT传感器网络，其中多个传感器通过继电器连接到相应的目标节点。因此，继电器计划传感器以示例和目标节点进行更新。中继可以每次选择多个传感器和目标节点。为了最大程度地减少平均加权总和AOI，研究了对继电器的采样和更新政策的联合优化。对于同样给予权重的无误和对称情况，可以找到必要的和足够的最佳条件。使用此结果，我们获得了封闭形式表达式中的最小平均总和AOI，可以将其解释为单个继电器网络中总和AOI的基本限制。另外，对于容易出错的情况和对称情况，我们已经证明，贪婪的策略可以达到目标节点的最低平均值AOI。对于一般情况，我们提出了通过强化学习获得的调度计划政策。
We consider IoT sensor network where multiple sensors are connected to corresponding destination nodes via a relay. Thus, the relay schedules sensors to sample and destination nodes to update. The relay can select multiple sensors and destination nodes in each time. In order to minimize average weighted sum AoI, joint optimization of sampling and updating policy of the relay is investigated. For errorless and symmetric case where weights are equally given, necessary and sufficient conditions for optimality is found. Using this result, we obtain that the minimum average sum AoI in a closed-form expression which can be interpreted as fundamental limit of sum AoI in a single relay network. Also, for error-prone and symmetric case, we have proved that greedy policy achieves the minimum average sum AoI at the destination nodes. For general case, we have proposed scheduling policy obtained via reinforcement learning.
