Wi-Fi Sensing: Should Mobiles Sleep Longer as They Age?

Abstract

An essential condition precedent to the success of mobile applications based on Wi-Fi (e.g., iCloud) is an energy- efficient Wi-Fi sensing. From a user’s perspective, a good Wi-Fi sensing policy should depend on both inter-AP arrival and contact duration time distributions. Prior work focuses on limited cases of those two distributions (e.g., exponential) or proposes heuristic approaches such as AI (Additive Increase). In this paper, we formulate a functional optimization problem on Wi-Fi sensing under general inter-AP and contact duration distributions, and propose how each user should sense Wi-Fi APs to strike a balance between energy efficiency and performance, depending on the users’ mobility pattern. To that end, we derive an optimal condition which sheds insights into the aging property, the key feature required by efficient Wi-Fi sensing polices. Guided by the analytical studies and the implications, we develop a new sensing algorithm, called WiSAG (Wi-Fi Sensing with AGing), which is demonstrated to outperform the existing sensing algorithms up to 47% through extensive trace-driven simulations using the real mobility traces gathered from smartphones.