Eywa: A General Framework for Scheduler Design in AoI Optimization
Chengzhang Li, Shaoran Li, Qingyu Liu, Y. Thomas Hou, Wenjing Lou, Sastry Kompella · IEEE Internet of Things Journal · 2025
Age of Information (AoI) is a metric that can be used to measure the freshness of information. Since its inception, there have been active research efforts on designing scheduling algorithms to AoI-related problems. These problems vary in specific AoI-based objectives and network settings. For each problem, typically a custom-designed scheduler was developed. Instead of following the (custom-design) path, we envision and pursue a general framework that can be applied to design a wide range of schedulers to solve AoI-related problems. As a first step toward this vision, we present a general framework—Eywa, that can be applied to construct high-performance schedulers for a family of AoI-related optimization and decision problems, all sharing a common setting of an IoT data collection network. We show how to apply Eywa to solve three important problems: to minimize weighted sum of AoIs, to minimize bandwidth requirement under AoI constraints, and to determine the existence of feasible schedulers to satisfy AoI constraints. We show that for each problem, Eywa can either offer a stronger performance guarantee than the state-of-the-art algorithms or provide new (or general) results that are not available in the literature.