An age of information based scheduling algorithm in a shared channel with energy and link capacity constraints

For data collection systems, it is important to rationally allocate link capacity to each source node so that the base station can receive fresh data. In recent years, a metric called age of information (AoI) has appeared to measure the freshness of the received information. In this paper, we build a model in which multiple heterogeneous source nodes with energy constraints transmit samples to a base station via a shared capacity-constrained channel. Then, with the objective of minimizing average weighted AoI in data collection systems, we propose a strategy where each source node has two buffers to store its latest partially transmitted sample and its complete latest collected sample, respectively. We establish the AoI model, sample transmission model and energy consumption model for the two buffers, and design a scheduling algorithm two-buffers strategy algorithm in this strategy. Finally, the proposed algorithm has been compared with the other four scheduling algorithms by simulation. The results show that the proposed algorithm performs better than them in terms of the average weighted AoI.