Age of Information (AoI), which measures the time elapsed since the generation of the last received packet at the destination, is a new metric for real-time status update tracking applications. In this paper, we consider a status-update system in which a source node samples updates and sends them to an edge server over a delay channel. The received updates are processed by the server with an infinite buffer and then delivered to a destination. The channel can send only one update at a time, and the server can process one at a time as well. The source node applies generate-at-will model according to the state of the channel, the edge server, and the buffer. We aim to minimize the average AoI with \emph{independent and identically distributed} transmission time and processing time. We consider three online scheduling policies. The first one is the optimal long wait policy, under which the source node only transmits a new packet after the old one is delivered. Secondly, we propose a peak age threshold policy, under which the source node determines the sending time based on the estimated peak age of information (PAoI). Finally, we improve the peak age threshold policy by considering a postponed plan to reduce the waiting time in the buffer. The AoI performance under these policies is illustrated by numerical results with different parameters.
翻译:信息时代( AoI) 用来测量在目的地生成上一个接收的软件包所花的时间, 是实时更新状态跟踪应用程序的新标准 。 在本文中, 我们考虑一个状态更新系统, 在该系统中, 源节点样本更新, 并通过延迟频道将其发送到边缘服务器 。 接收的更新由服务器处理, 带有无限的缓冲, 然后发送到目的地 。 频道只能一次发送一次更新, 服务器也可以一次处理一次 。 源节点根据频道、 边缘服务器和缓冲的状态应用生成- 动态模型 。 我们的目标是将平均 AoI 的传输时间和处理时间减少到最低 。 我们考虑三个在线列表政策 。 第一个是最佳的等待时间政策, 根据此政策, 源节点只能在旧的发送后传送新包 。 第二, 我们提出一个峰值年龄门槛政策, 根据该政策, 源节点根据信息估计的峰值、 边际服务器和缓冲时间 来决定发送时间 。 最后, 我们根据缓冲政策改进了平均 A 的缓冲值 政策 。 根据这些缓冲计划, 我们根据缓冲 的缓冲 改进了这些缓冲 的缓冲 度 政策 。