Minimizing Age of Information for Mobile Edge Computing Empowered Industrial Internet of Things
Jiaping Li, Jianhua Tang, Zilong Liu · 2022
In the Industrial Internet of Things (IIoT), the freshness of information plays a vital role to ensure quality and timely delivery of data services. In this paper, we use age of information (AoI) as the metric. To reduce the AoI, we leverage mobile edge computing (MEC) to partially offload information to the edge server. In addition, the feature of short packet communication in IIoT is also considered in this work. We derive the closed-form expression of average AoI under the standard automatic repeat request (ARQ) protocol with zero-wait policy, and then formulate the average AoI minimization problem by jointly optimizing the short packet blocklength and MEC offloading ratio. Due to the nonconvexity nature of the problem, we tackle it by employing block coordinate descent (BCD) and successive convex approximation (SCA) methods to solve it and then prove their convergence. Our numerical results show that the optimal average AoI yielded by our proposed approach is almost identical to the high-complexity exhaustive search method, and has significant improvement over the benchmark methods. Furthermore, from the AoI perspective, the optimal strategy tends to offload all information to edge server when the computing capacity of local device is less than a threshold.