Optimal Information Update for Energy Harvesting Sensor with Reliable Backup Energy

Abstract

The timely delivery of status information collected from sensors is critical in many real-time applications, e.g., monitoring and control. In this paper, we consider a scenario where a wireless sensor sends updates to the destination over an erasure channel with the supply of harvested energy and reliable backup energy. We adopt the metric age of information (AoI) to measure the timeliness of the received updates at the destination. We aim to find the optimal information updating policy that minimizes the time-average weighted sum of the AoI and the reliable backup energy cost. First, when all the environmental statistics are assumed to be known, the optimal information updating policy exists and is proved to have a threshold structure. Based on this special structure, an algorithm for efficiently computing the optimal policy is proposed. Then, for the unknown environment, a learning-based algorithm is employed to find a near-optimal policy. The simulation results verify the correctness of the theoretical derivation and the effectiveness of the proposed method.

Age of Synchronization Minimization Algorithms in Wireless Networks with Random Updates under Throughput Constraints

“…To evaluate the freshness of status updates, researchers have introduced the concept of the age of information (AoI) [ 1 ], which is defined as the time elapsed since the the generation of the most recent status update. Previous studies [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ] have focused on developing scheduling algorithms that minimize the average AoI across the network in the generate-at-will scenario, which means the generation of status update packets can be controlled. Various low-complexity algorithms were presented in [ 2 ] to minimize the average AoI in the network, demonstrating their proximity to the theoretical lower bound.…”