Modeling and analysis of energy conservation scheme based on duty cycling in wireless ad hoc sensor network

Sensors (Basel). 2010;10(6):5569-89. doi: 10.3390/s100605569. Epub 2010 Jun 3.

Abstract

In sensor network, energy conservation is one of the most critical issues since sensor nodes should perform a sensing task for a long time (e.g., lasting a few years) but the battery of them cannot be replaced in most practical situations. For this purpose, numerous energy conservation schemes have been proposed and duty cycling scheme is considered the most suitable power conservation technique, where sensor nodes alternate between states having different levels of power consumption. In order to analyze the energy consumption of energy conservation scheme based on duty cycling, it is essential to obtain the probability of each state. In this paper, we analytically derive steady state probability of sensor node states, i.e., sleep, listen, and active states, based on traffic characteristics and timer values, i.e., sleep timer, listen timer, and active timer. The effect of traffic characteristics and timer values on the steady state probability and energy consumption is analyzed in detail. Our work can provide sensor network operators guideline for selecting appropriate timer values for efficient energy conservation. The analytical methodology developed in this paper can be extended to other energy conservation schemes based on duty cycling with different sensor node states, without much difficulty.

Keywords: duty cycling; energy conservation; energy consumption; sensor network; steady state probability.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Computer Communication Networks / instrumentation
  • Conservation of Energy Resources / methods*
  • Humans
  • Models, Biological
  • Models, Theoretical*
  • Periodicity
  • Remote Sensing Technology / instrumentation*
  • Signal Processing, Computer-Assisted / instrumentation
  • Wireless Technology / instrumentation*
  • Workload*