Open Access

Opportunistic Carrier Sensing for Energy-Efficient Information Retrieval in Sensor Networks

EURASIP Journal on Wireless Communications and Networking20052005:125040

DOI: 10.1155/WCN.2005.231

Received: 26 January 2005

Published: 28 April 2005


We consider distributed information retrieval for sensor networks with cluster heads or mobile access points. The performance metric used in the design is energy efficiency defined as the ratio of the average number of bits reliably retrieved by the access point to the total amount of energy consumed. A distributed opportunistic transmission protocol is proposed using a combination of carrier sensing and backoff strategy that incorporates channel state information (CSI) of individual sensors. By selecting a set of sensors with the best channel states to transmit, the proposed protocol achieves the upper bound on energy efficiency when the signal propagation delay is negligible. For networks with substantial propagation delays, a backoff function optimized for energy efficiency is proposed. The design of this backoff function utilizes properties of extreme statistics and is shown to have mild performance loss in practical scenarios. We also demonstrate that opportunistic strategies that use CSI may not be optimal when channel acquisition at individual sensors consumes substantial energy. We show further that there is an optimal sensor density for which the opportunistic information retrieval is the most energy efficient. This observation leads to the design of the optimal sensor duty cycle.


sensor networks distributed information retrieval opportunistic transmission energy efficiency

Authors’ Affiliations

Department of Electrical and Computer Engineering, University of California
School of Electrical and Computer Engineering, Cornell University


© Zhao and Tong 2005

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.