Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
Name
2019MobiHocTechRep.pdf
Description
Accepted version
Size
1.16 MB
Format
Adobe PDF
Checksum (MD5)
443094d6ed1f5d438c5b8ec6171b16ef
Author(s)
Kadota, Igor
Modiano, Eytan H
Date Issued
July 2019
Journal
Mobihoc ’19
Publisher
Association for Computing Machinery (ACM)
Citation
Kadota, Igor and Eytan Modiano. “Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals.” Paper presented at Mobihoc ’19, Catania, Italy, July 2-5 2019, Association for Computing Machinery (ACM) © 2019 The Author(s)
Version
Author's final manuscript
Abstract
We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1145/3323679.3326520
