Online energy-saving algorithm for sensor networks in dynamic changing environments

  • Authors:
  • Meikang Qiu;Min Chen;Meiqin Liu;Shaobo Liu;Jiayin Li;Xue Liu;Yongxin Zhu

  • Affiliations:
  • (Correspd. E-mail: mqiu@engr.uky.edu) Department of Electrical and Computer Engineering University of Kentucky, Lexington, KY, USA;School of Computer Science and Engineering, Seoul National University, 151-742, Korea;College of Electrical Engineering, Zhejiang University, Yuquan Campus, Hangzhou 310027, P.R. China;Department of Electrical and Computer Engineering, State University of New York at Binghamton, USA;Department of Electrical and Computer Engineering University of Kentucky, Lexington, KY, USA;Department of Computer Science and Engineering, University of Nebraska-Lincoln, USA;School of Microelectronic, Shanghai Jiaotong University, Shanghai 200240, P.R. China

  • Venue:
  • Journal of Embedded Computing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

How to save energy is a critical issue for the life time of sensor networks. Under continuously changing environments, sensor nodes have varying sampling rates. In this paper, we present an online algorithm to minimize the total energy consumption while satisfying sampling rate with guaranteed probability. We model the sampling rate as a random variable, which is estimated over a finite time window. An efficient algorithm, EOSP (Energy-aware Online algorithm to satisfy Sampling rates with guaranteed Probability), is proposed. Our approach can adapt the architecture accordingly to save energy. Experimental results demonstrate the effectiveness of our approach.