DEAL: discover and exploit asymmetric links in dense wireless sensor networks

  • Authors:

  • Bin Bin Chen;Shuai Hao;Mingze Zhang;Mun Choon Chan;A. L. Ananda

  • Affiliations:

  • School of Computing, National University of Singapore;Computer Science Department, University of Southern California;School of Computing, National University of Singapore;School of Computing, National University of Singapore;School of Computing, National University of Singapore

  • Venue:
  • SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Asymmetric links commonly exist in low power wireless sensor networks. However, it is difficult to discover and exploit them efficiently. In this work, we propose DEAL, a link management scheme to Discover and Exploit Asymmetric Links efficiently in dense wireless sensor networks. Equipped with a novel feedback mechanism, DEAL dynamically adapts its link maintenance mechanism based on the estimated link quality, and manages the (small) neighbor table so as to retain the most useful information. We implement DEAL in TinyOS and evaluate its performance using both TOSSIM and testbed. The simulation results show that more than 80% of asymmetric links can be discovered and maintained with minimum overhead. Using a collection tree application and ETX as the routing metric, the average path ETX can be reduced by up to 20%. Testbed evaluation also shows that DEAL improves the network routing performance by identifying useful asymmetric links.