论文标题
关于在能量收获IoT网络中部分电池知识下放松的年龄优化 - 然后截断的方法
On the Age-Optimality of Relax-then-Truncate Approach under Partial Battery Knowledge in Energy Harvesting IoT Networks
论文作者
论文摘要
我们考虑一个能量收集（EH）IoT网络，用户向启用缓存的边缘节点向按需请求发送有关各种随机过程的状态更新，每个过程由EH传感器监视。 Edge节点通过指示相应的传感器发送新的状态更新或从缓存中检索最近收到的测量方法来服务用户的请求。我们的目标是在边缘节点上找到一个控制策略，以最大程度地减少所有传感器的平均按点数AOI，但在边缘节点处的部分电池知识下受到每插槽传输和能量限制。也就是说，有限的无线电资源（例如，带宽）导致只有有限数量的传感器才能在每个时间插槽（即每插槽传输约束）和EH传感器的能量稀缺下发送状态更新。此外，仅通过接收的状态更新数据包，将Edge节点告知传感器的电池电量，从而导致了对决策制定电池电量的不确定性。我们开发出一种低复杂性算法 - 称为放松，然后截断 - 并证明它是不可能的，因为传感器的数量是无限的。数值结果表明，所提出的方法在申请意识的贪婪政策上取得了巨大的收益，并表明即使对于中等数量的传感器，它也具有几乎最佳的性能。
We consider an energy harvesting (EH) IoT network, where users make on-demand requests to a cache-enabled edge node to send status updates about various random processes, each monitored by an EH sensor. The edge node serves users' requests by either commanding the corresponding sensor to send a fresh status update or retrieving the most recently received measurement from the cache. We aim to find a control policy at the edge node that minimizes the average on-demand AoI over all sensors subject to per-slot transmission and energy constraints under partial battery knowledge at the edge node. Namely, the limited radio resources (e.g., bandwidth) causes that only a limited number of sensors can send status updates at each time slot (i.e., per-slot transmission constraint) and the scarcity of energy for the EH sensors imposes an energy constraint. Besides, the edge node is informed of the sensors' battery levels only via received status update packets, leading to uncertainty about the battery levels for the decision-making.We develop a low-complexity algorithm -- termed relax-then-truncate -- and prove that it is asymptotically optimal as the number of sensors goes to infinity. Numerical results illustrate that the proposed method achieves significant gains over a request-aware greedy policy and show that it has near-optimal performance even for moderate numbers of sensors.
