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

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. The authors 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. The approach can adapt the architecture accordingly to save energy. Experimental results demonstrate the effectiveness of the approach.