A trade-off between energy and delay in data dissemination for wireless sensor networks using transmission range slicing

  • Authors:

  • Habib M. Ammari;Sajal K. Das

  • Affiliations:

  • Center for Research in Wireless Mobility and Networking (CReWMaN), Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA;Center for Research in Wireless Mobility and Networking (CReWMaN), Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA

  • Venue:
  • Computer Communications
  • Year:
  • 2008

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Abstract

Data dissemination is an essential function in wireless sensor networks (WSNs). A WSN consists of a large number of unattended sensors with limited storage, battery power, computation, and communication capabilities, where battery power (or energy) is the most crucial resource for sensor nodes. Because delay time is also a critical metric for certain applications, data dissemination between source sensors (or simply sources) and a sink (or central gathering point) should be done in an energy-efficient and timely manner. In this paper, we present an approach that characterizes a trade-off between energy and source-to-sink delay (or simply delay). Specifically, we decompose the transmission range of sensors into concentric circular bands (CCBs) based on a minimum transmission distance between any pair of sensors. Our decomposition strategy provides a classification of these CCBs that helps a sensor express its degree of interest (DoI) in minimizing two conflicting metrics, namely energy consumption and delay. We also propose a data dissemination protocol that exploits the above-mentioned decomposition to meet the specific requirements of a sensing application in terms of energy and delay. We prove that the use of sensors nodes, which lie on or closely to the shortest path between a source and a sink, as proxy forwarders in data dissemination from sources to a sink, helps simultaneously minimize energy consumption and delay. Also, we compute theoretical lower and upper bounds on these two metrics. Our simulation results are found to be consistent with our theoretical results, and show that the first CCB minimizes energy consumption; the last CCB minimizes delay; and the middle CCBs trade-off energy consumption with delay in data dissemination in WSNs.