Optimizing Information Freshness using Low-Power Status Updates via Sleep-Wake Scheduling
Abstract
In this paper, we consider the problem of optimizing the freshness of status updates that are sent from a large number of low-power source nodes to a common access point. The source nodes utilize carrier sensing to reduce collisions and adopt an asychronized sleep-wake strategy to achieve an extended battery lifetime (e.g., 10-25 years). We use age of information (AoI) to measure the freshness of status updates, and design the sleep-wake parameters for minimizing the weighted-sum peak AoI of the sources, subject to per-source battery lifetime constraints. When the sensing time is zero, this sleep-wake design problem can be solved by resorting to nested convex optimization; however, for positive sensing times, the problem is non-convex. We devise a low-complexity solution to solve this problem and prove that, for practical sensing times, the solution is within a small gap from the optimum AoI performance. Our numerical and NS-3 simulation results show that our solution can indeed elongate the batteries lifetime of information sources, while providing a competitive AoI performance.
Keywords
Cite
@article{arxiv.1910.00205,
title = {Optimizing Information Freshness using Low-Power Status Updates via Sleep-Wake Scheduling},
author = {Ahmed M. Bedewy and Yin Sun and Rahul Singh and Ness B. Shroff},
journal= {arXiv preprint arXiv:1910.00205},
year = {2019}
}