Taming the Tail of Maximal Information Age in Wireless Industrial Networks

Abstract

In wireless industrial networks, the information of time-sensitive control systems needs to be transmitted in an ultra-reliable and low-latency manner. This letter studies the resource allocation problem in finite blocklength transmission, in which the information freshness is measured as the age of information (AoI) whose maximal AoI is characterized using extreme value theory (EVT). The considered system design is to minimize the sensors' transmit power and transmission blocklength subject to constraints on the maximal AoI's tail behavior. The studied problem is solved using Lyapunov stochastic optimization, and a dynamic reliability and age-aware policy for resource allocation and status updates is proposed. Simulation results validate the effectiveness of using EVT to characterize the maximal AoI. It is shown that sensors need to send larger-size data with longer transmission blocklength at lower transmit power. Moreover, the maximal AoI's tail decays faster at the expense of higher average information age.

Accepted in the IEEE Communications Letters with 6 pages and 5 figures

References in corpus (2)

• Ultra-Reliable and Low-Latency Vehicular Transmission: An Extreme Value Theory Approach
• Ultra-Reliable Low-Latency Vehicular Networks: Taming the Age of Information Tail

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• Risk-Aware Optimization of Age of Information in the Internet of Things
• Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT