Analysis and Optimization of Age of Information for Area Sensing

The Age of Information (AoI) is viewed as a key performance metric in real-time applications. This letter focuses on the analysis and optimization of AoI in the context of area sensing. First, we develop a model for an omnidirectional sensing system and divide the entire area into multiple sub-areas. Then, the analytical expression of the average AoI for each sub-area is derived by modelling the evolution process of the instantaneous AoI for each sub-area as a Discrete-Time Markov Chain (DTMC). Finally, we formulate two optimization problems, one based on the min-max criterion and the other on the sum-optimal criterion. The former is solved analytically, and the latter is a sum-of-ratios minimization fractional programming (min-FP) problem, which is solved by an alternating iterative algorithm. Simulation results verify the accuracy of our analytical results of the average AoI and demonstrate the effectiveness of our solutions in addressing the two optimization problems.