# Online Energy-Efficient Scheduling for Timely Information Downloads in Mobile Networks

## TL;DR

This paper proposes a randomized online scheduling algorithm for mobile devices that balances information freshness and energy consumption, achieving near-optimal performance despite unpredictable mobility and channel dynamics.

## Contribution

It introduces a novel online scheduling algorithm that guarantees a competitive ratio of approximately 1.58 for energy-efficient, timely information updates in mobile networks.

## Key findings

- Expected total cost is at most 1.58 times the offline optimal.
- Algorithm adapts to arbitrary mobility and non-stationary channels.
- Balances age of information with energy consumption effectively.

## Abstract

We consider a mobile network where a mobile device is running an application that requires timely information. The information at the device can be updated by downloading the latest information through neighboring access points. The freshness of the information at the device is characterized by the recently proposed age of information. However, minimizing the age of information by frequent downloading increases power consumption of the device. In this context, an energy-efficient scheduling algorithm for timely information downloads is critical, especially for power-limited mobile devices. Moreover, unpredictable movement of the mobile device causes uncertainty of the channel dynamics, which is even non-stationary within a finite amount of time for running the application. Thus, in this paper we devise a randomized online scheduling algorithm for mobile devices, which can move arbitrarily and run the application for any amount of time. We show that the expected total cost incurred by the proposed algorithm, including an age cost and a downloading cost, is (asymptotically) at most e/(e-1) ~ 1.58 times the minimum total cost achieved by an optimal offline scheduling algorithm.