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Optimizing Information Freshness in Wireless Networks: A Stochastic Geometry Approach

Author(s): Yang, Howard H; Arafa, Ahmed; Quek, Tony QS; Poor, H Vincent

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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' 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, for the design of a decentralized scheduling policy that exploits local observation to make transmission decisions that minimize the AoI. To quantify the performance, we also derive accurate and tractable expressions for the peak AoI. Numerical results reveal that: i) the packet arrival rate directly affects the service process due to queueing interactions, ii) the proposed scheme can adapt to traffic variations and largely reduce the peak AoI, and iii) the proposed scheme scales well as the network grows in size. This is done by adaptively adjusting the radio access probability at each transmitter to the change of the ambient environment.
Publication Date: 28-Feb-2020
Citation: Yang, Howard H, Arafa, Ahmed, Quek, Tony QS, Poor, H Vincent. (2021). Optimizing Information Freshness in Wireless Networks: A Stochastic Geometry Approach. IEEE Transactions on Mobile Computing, 20 (6), 2269 - 2280. doi:10.1109/tmc.2020.2977010
DOI: doi:10.1109/tmc.2020.2977010
ISSN: 1536-1233
EISSN: 1558-0660
Pages: 2269 - 2280
Type of Material: Journal Article
Journal/Proceeding Title: IEEE Transactions on Mobile Computing
Version: Author's manuscript

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