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M. Moltafet, M. Leinonen and M. Codreanu, "Worst Case Age of Information in Wireless Sensor Networks: A Multi-Access Channel," in IEEE Wireless Communications Letters, vol. 9, no. 3, pp. 321-325, March 2020.

Worst case age of information in wireless sensor networks : a multi-access channel

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Author: Moltafet, Mohammad1; Leinonen, Markus1; Codreanu, Marian2
Organizations: 1Centre for Wireless Communications–Radio Technologies, University of Oulu, 90014 Oulu, Finland
2Department of Science and Technology, Link¨oping University, Sweden
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019121348054
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2019-12-13
Description:

Abstract

Freshness of status update packets is essential for enabling a wide range of applications in wireless sensor networks (WSNs). Accordingly, we consider a WSN where sensors communicate status updates to a destination by contending for the channel access based on a carrier sense multiple access (CSMA) method. We analyze the worst case average age of information (AoI) and average peak AoI from the view of one sensor in a system where all the other sensors have a saturated queue. Numerical results illustrate the importance of optimizing the contention window size and the packet arrival rate to maximize the information freshness.

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Series: IEEE wireless communications letters
ISSN: 2162-2337
ISSN-E: 2162-2345
ISSN-L: 2162-2337
Volume: 9
Issue: 3
Pages: 321 - 325
DOI: 10.1109/LWC.2019.2953628
OADOI: https://oadoi.org/10.1109/LWC.2019.2953628
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Age of information (AoI)
CSMA/CA
M/G/1 queueing model
multi-access channel
Article
Funding: This research has been financially supported by the Infotech Oulu and the Academy of Finland grant No. 323698. M. Codreanu would like to acknowledge the support of the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 793402 (COMPRESS NETS). This research has also been financially supported by Academy of Finland 6Genesis Flagship (grant 318927). M. Moltafet would like to acknowledge the support of Finnish Foundation for Technology Promotion.
Academy of Finland Grant Number: 323698
318927
Detailed Information: 323698 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
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