A Novel Scheduling Strategy in Priority-Aware IoT Networks for Age of Information Optimization

We propose a novel scheduling strategy for prioritization-critical time-sensitive Internet of things (IoT) networks. The goal is to decrease the number of sensors with outdated information and minimize the difference between their age of information (AoI) and the specified limit, within a resource-constrained environment. The proposed approach relies on reformulating the original problem as a knapsack problem. This novel method is shown to outperform benchmarks to satisfy the needs of priority-aware IoT networks.