Adaptive routing for sensor networks using reinforcement learning

Wang Ping, Wang Ting

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

39 Scopus citations

Abstract

Efficient and robust routing is central to wireless sensor networks (WSN) that feature energy-constrained nodes, unreliable links, and frequent topology change. While most existing routing techniques are designed to reduce routing cost by optimizing one goal, e.g., routing path length, load balance, re-transmission rate, etc, in real scenarios however, these factors affect the routing performance in a complex way, leading to the need of a more sophisticated scheme that makes correct trade-offs. In this paper, we present a novel routing scheme, AdaR that adaptively learns an optimal routing strategy, depending on multiple optimization goals. We base our approach on a least squares reinforcement learning technique, which is both data efficient, and insensitive against initial setting, thus ideal for the context of ad-hoc sensor networks. Experimental results suggest a significant performance gain over a naïve Q-learning based implementation.

Original languageEnglish (US)
Title of host publicationProceedings - Sixth IEEE International Conference on Computer and Information Technology, CIT 2006
PublisherIEEE Computer Society
Pages219
Number of pages1
ISBN (Print)076952687X, 9780769526874
DOIs
StatePublished - 2006
Event6th IEEE International Conference on Computer and Information Technology, CIT 2006 - Seoul, Korea, Republic of
Duration: Sep 20 2006Sep 22 2006

Publication series

NameProceedings - Sixth IEEE International Conference on Computer and Information Technology, CIT 2006

Conference

Conference6th IEEE International Conference on Computer and Information Technology, CIT 2006
CountryKorea, Republic of
CitySeoul
Period9/20/069/22/06

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Software
  • Mathematics(all)

Fingerprint Dive into the research topics of 'Adaptive routing for sensor networks using reinforcement learning'. Together they form a unique fingerprint.

Cite this