论文标题
通过Edge Computing进行AOI最小化的传输和处理的在线安排
Online Scheduling of Transmission and Processing for AoI Minimization with Edge Computing
论文作者
论文摘要
信息年龄（AOI）衡量以来目的地上次收到的数据包以来经过的时间，是实时状态更新跟踪应用程序的新指标。在本文中，我们考虑了一个状态上的系统，在该系统中，源节点示例更新并通过延迟通道将其发送到边缘服务器。接收到的更新由服务器使用无限缓冲区处理，然后交付到目的地。该频道一次只能发送一个更新，并且服务器也可以一次处理一个更新。源节点根据频道，边缘服务器和缓冲区的状态应用将生成的模型。我们的目标是使用\ emph {独立且相同分布的传输时间和处理时间最小化平均AOI。我们考虑三个在线调度策略。第一个是最佳的长期等待策略，在该策略下，源节点仅在传递旧数据包后才传输一个新数据包。其次，我们提出了一个峰值年龄阈值策略，根据该政策，源节点根据估计的信息年龄（PAOI）确定发送时间。最后，我们通过考虑将缓冲区中的等待时间的推迟计划提高了峰值年龄阈值政策。这些策略下的AOI性能通过具有不同参数的数值结果来说明。
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.
