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.
This work is partially supported by TI University Program, NSF EIA-0103709, Texas ARP 009741-0028-2001, NSF CCR-0309461, NSF IIS-0513669, and Microsoft, USA.
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Qiu, M., Sha, E.H.M. (2007). Energy-Aware Online Algorithm to Satisfy Sampling Rates with Guaranteed Probability for Sensor Applications. In: Perrott, R., Chapman, B.M., Subhlok, J., de Mello, R.F., Yang, L.T. (eds) High Performance Computing and Communications. HPCC 2007. Lecture Notes in Computer Science, vol 4782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75444-2_20
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DOI: https://doi.org/10.1007/978-3-540-75444-2_20
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