Second-Order Analysis of CSMA Protocols for Age-of-Information Minimization

This paper introduces a general framework to analyze and optimize age-of-information (AoI) in CSMA protocols for distributed uplink transmissions. The proposed framework combines two theoretical approaches. First, it employs second-order analysis that characterizes all random processes by their respective means and temporal variances and approximates AoI as a function of the mean and temporal variance of the packet delivery process. Second, it employs mean-field approximation to derive the mean and temporal variance of the packet delivery process for one node in the presence of interference from others. To demonstrate the utility of this framework, this paper applies it to the age-threshold ALOHA policy and identifies parameter settings that outperform those previously suggested as optimal in the original work that introduced this policy. Simulation results demonstrate that our framework provides precise AoI approximations and achieves significantly better performance, even in networks with a small number of users.

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Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10943050
Primary Topic
Age of Information Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Second-Order Analysis of CSMA Protocols for Age-of-Information Minimization

Siqi Fan, I-Hong Hou
Age of Information Optimization
article

Second-Order Analysis of CSMA Protocols for Age-of-Information Minimization

Siqi Fan, I-Hong Hou
article en

Abstract

This paper introduces a general framework to analyze and optimize age-of-information (AoI) in CSMA protocols for distributed uplink transmissions. The proposed framework combines two theoretical approaches. First, it employs second-order analysis that characterizes all random processes by their respective means and temporal variances and approximates AoI as a function of the mean and temporal variance of the packet delivery process. Second, it employs mean-field approximation to derive the mean and temporal variance of the packet delivery process for one node in the presence of interference from others. To demonstrate the utility of this framework, this paper applies it to the age-threshold ALOHA policy and identifies parameter settings that outperform those previously suggested as optimal in the original work that introduced this policy. Simulation results demonstrate that our framework provides precise AoI approximations and achieves significantly better performance, even in networks with a small number of users.

Texas A&M University (US)
National Science Foundation, High Performance Research Computing, Texas A and M University, Office of Naval Research, Army Research Office
Openalex Percentile: Top 65%
Age of Information Optimization
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