Affiliations: 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 Computer Science and Engineering,
University of Nebraska-Lincoln, USA | School of Microelectronic, Shanghai Jiaotong
University, Shanghai 200240, P.R. China
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.