Cited by 101Energy Efficient Wireless Sensor NetworksSecurity in Wireless Sensor NetworksMobile Ad Hoc Networks

Predicting link quality using supervised learning in wireless sensor networks

Wang, Yong, Martonosi, Margaret, Peh, Li-Shiuan·2007·ACM SIGMOBILE Mobile Computing and Communications Review

Abstract

Routing protocols in sensor networks maintain information on neighbor states and potentially many other factors in order to make informed decisions. Challenges arise both in (a) performing accurate and adaptive information discovery and (b) processing/analyzing the gathered data to extract useful features and correlations. To address such challenges, this paper explores using supervised learning techniques to make informed decisions in the context of wireless sensor networks. We investigate the design space of both offline learning and online learning and use link quality estimation as a case study to evaluate their effectiveness. For this purpose, we present MetricMap, a metric-based collection routing protocol atop MintRoute that derives link quality using classifiers learned in the training phase, when the traditional ETX approach fails. The offline learning approach is evaluated on a 30-node sensor network testbed, and our results show that MetricMap can achieve up to 300% improvement over MintRoute in data delivery rate for high data rate situations, with no negative impact on other performance metrics. We also explore the possibility of using online learning in this paper.

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Crossref · 10.1145/1317425.1317434

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Authors
Wang, Y., Martonosi, M., & Peh, L.-S.
Affiliations
Princeton University (US)
Venue
ACM SIGMOBILE Mobile Computing and Communications Review
Published
2007-07
Volume
11
Issue
3
Pages
71-83
ISSN
  • 1559-1662 (ISSN-L)
  • 1931-1222
OpenAlex
W2037928371
Cited by
101
References
39
Citations by year
2026: 1 · 2025: 5 · 2024: 4 · 2023: 1 · 2022: 5 · 2021: 9 · 2020: 13 · 2019: 6 · 2018: 8 · 2017: 9 · 2016: 4 · 2015: 3 · 2014: 8 · 2013: 5 · 2012: 6
FWCI
4.78
Type
journal article
Language
en
Open access
closed
Locations
ACM SIGMOBILE Mobile Computing and Communications Review (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Mobile Ad Hoc Networks
Keywords
link quality estimation, wireless sensor networks, routing protocols, supervised learning, ETX, online learning, offline learning, data delivery ratio

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