Optimizing Information Freshness using Low-Power Status Updates via Sleep-Wake Scheduling

TL;DR

This paper proposes a sleep-wake scheduling strategy for low-power sources to optimize information freshness, balancing battery life and AoI, with a low-complexity solution proven near-optimal for practical sensing times.

Contribution

It introduces a novel sleep-wake parameter design for minimizing peak AoI under battery constraints, including a low-complexity solution for non-convex cases.

Findings

The proposed method extends battery lifetime significantly.

It achieves near-optimal AoI performance in practical scenarios.

Simulation results validate the effectiveness of the approach.

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.