Minimizing Age-of-Information With Joint Transmission and Computing Scheduling in Mobile-Edge Computing

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 Internet of Things (IoT) applications. In many applications, status information needs to be extracted through computation, which can be processed at an edge server enabled by mobile-edge computing (MEC). In this article, we consider a status update system with MEC in an offline scenario, where transmission and computation need to be jointly scheduled to minimize AoI. Usually, long queuing delay and large packet generation interval will increase age in the queuing system. Therefore, a reasonable scheduling policy is the no-wait policy, which achieves zero queuing delay and a low generation interval. However, the no-wait policy is not always optimal. We propose an interval-wait policy that allows nonzero queuing delay and study the average age minimization problem in this policy. Theoretical results show that the optimal interval-wait policy has a special structure: the queuing delay is either zero or a fixed value that is determined by the transmission and computation time duration of the packet itself and its adjacency. Based on this, we propose an efficient enumerating-based algorithm to compute the optimal interval-wait policy. Our experimental results show that: 1) the interval-wait policy achieves optimal performance in most cases and 2) our proposed efficient algorithm can find the optimal interval-wait policy.