Energy-Aware Online Algorithm to Satisfy Sampling Rates with Guaranteed Probability for Sensor Applications

Abstract. Energy consumption is a major factor that limits the performance of sensor applications. Sensor nodes have varying sampling rates since they face continuously changing environments. In this paper, the sampling rate is modeled as a random variable, which is estimated over a finite time window. We presents an online algorithm to minimize the total energy consumption while satisfying sampling rate with guaranteed probability. 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.

• Type: Conference
• Year: 2007
• Where: HPCC
• Authors: Meikang Qiu, Edwin Hsing-Mean Sha
• Keywords: Distributed And Parallel Computing, Energy Consumption, HPCC 2007, Online Algorithm, Sampling Rates