@inproceedings{fed657d707ca4f9a9a9437d35b7118ab,
title = "Locally adaptive scheduling policy for optimizing information freshness in wireless networks",
abstract = "Optimization of information freshness in wireless networks has usually been performed based on queueing analysis that captures only the temporal traffic dynamics associated with the transmitters and receivers. However, the effect of interference, which is mainly dominated by the interferers{\^a}{\texttrademark} geographic locations, is not well understood. In this paper, we leverage a spatiotemporal model, which allows one to characterize the age of information (AoI) from a joint queueing-geometry perspective, and design a decentralized scheduling policy that exploits local observation to make transmission decisions that minimize the AoI. Simulation results reveal that the proposed scheme not only largely reduces the peak AoI but also scales well with the network size.",
author = "Yang, {Howard H.} and Ahmed Arafa and Quek, {Tony Q.S.} and Poor, {H. Vincent}",
year = "2019",
month = dec,
doi = "10.1109/GLOBECOM38437.2019.9013514",
language = "English (US)",
series = "2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings",
address = "United States",
note = "2019 IEEE Global Communications Conference, GLOBECOM 2019 ; Conference date: 09-12-2019 Through 13-12-2019",
}