A supervised learning approach for routing optimizations in wireless sensor networks

Yona Wang, Margaret Rose Martonosi, Li Shiuan Peh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Routing in sensor networks maintains 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. In this paper, we explore using supervised learning techniques to address such challenges in wireless sensor networks. Machine learning has been very effective in discovering relations between attributes and extracting knowledge and patterns using a large corpus of samples. As a case study, we use link quality prediction to demonstrate the effectiveness of our approach. For this purpose, we present MetricMap, a link-quality aware collection protocol atop MintRoute that derives link quality information using knowledge acquired from a training phase. Our approach allows MetricMap to maintain efficient routing in situations where traditional approaches fail. Evaluation on a 30-node sensor network testbed shows that MetricMap can achieve up to 300% improvement on data delivery rate in a high data-rate application, with no negative impact on other performance metrics, such as data latency. Our approach is based on real-world measurement and provides a new perspective to routing optimizations in wireless sensor networks.

Original languageEnglish (US)
Title of host publicationREALMAN 2006 - Proceedings of Second International Workshop on Multi-hop Ad Hoc Networks
Subtitle of host publicationfrom Theory to Reality
PublisherAssociation for Computing Machinery
Pages79-86
Number of pages8
ISBN (Print)1595933603, 9781595933607
DOIs
StatePublished - Jan 1 2006
EventREALMAN 2006 - 2nd International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality - Florence, Italy
Duration: May 26 2006May 26 2006

Publication series

NameREALMAN 2006 - Proceedings of Second International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality
Volume2006

Other

OtherREALMAN 2006 - 2nd International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality
CountryItaly
CityFlorence
Period5/26/065/26/06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Keywords

  • Classification
  • Link quality
  • Sensor networks
  • Supervised learning

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