@InProceedings{8553276,
  author = {L. Yang and H. Zhu and H. Wang and K. Kang and H. Qian},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Optimal Estimation with Extended Battery Life in Wireless Sensor Networks},
  year = {2018},
  pages = {662-666},
  abstract = {Energy constraint is always a bottleneck in a distributed wireless sensor network (WSN). Online censoring is an effective approach to reduce the overall power consumption by only transmitting statistical informative data. However, individual sensor may still suffer from energy shortage due to frequent transmission of informative data or geographical long distance transmission. In this paper, we consider the parameters estimation problem in WSNs, where the goal is to minimize the estimation error while keeping the network lifetime long. A distributed censoring algorithm is developed, which allows sensor nodes to make autonomous decisions on whether to transmit the sampled data. We show that with the proposed algorithm, the network lifetime extends and approaches to its theoretical limit, and the performance loss in terms of the estimation error is minimal. Simulation results validate its effectiveness.},
  keywords = {estimation theory;parameter estimation;statistical analysis;telecommunication network reliability;wireless sensor networks;distributed wireless sensor network;parameter estimation problem;statistical informative data transmission;optimal estimation error minimization;distributed censoring algorithm;network lifetime;geographical long distance transmission;energy shortage;statistical informative data;power consumption;WSN;extended battery life;Wireless sensor networks;Signal processing algorithms;Signal processing;Batteries;Estimation error;Energy consumption;Wireless sensor networks;censoring;network lifetime},
  doi = {10.23919/EUSIPCO.2018.8553276},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570434025.pdf},
}

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Online censoring is an effective approach to reduce the overall power consumption by only transmitting statistical informative data. However, individual sensor may still suffer from energy shortage due to frequent transmission of informative data or geographical long distance transmission. In this paper, we consider the parameters estimation problem in WSNs, where the goal is to minimize the estimation error while keeping the network lifetime long. A distributed censoring algorithm is developed, which allows sensor nodes to make autonomous decisions on whether to transmit the sampled data. We show that with the proposed algorithm, the network lifetime extends and approaches to its theoretical limit, and the performance loss in terms of the estimation error is minimal. Simulation results validate its effectiveness.","keywords":"estimation theory;parameter estimation;statistical analysis;telecommunication network reliability;wireless sensor networks;distributed wireless sensor network;parameter estimation problem;statistical informative data transmission;optimal estimation error minimization;distributed censoring algorithm;network lifetime;geographical long distance transmission;energy shortage;statistical informative data;power consumption;WSN;extended battery life;Wireless sensor networks;Signal processing algorithms;Signal processing;Batteries;Estimation error;Energy consumption;Wireless sensor networks;censoring;network lifetime","doi":"10.23919/EUSIPCO.2018.8553276","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570434025.pdf","bibtex":"@InProceedings{8553276,\n author = {L. Yang and H. Zhu and H. Wang and K. Kang and H. Qian},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Optimal Estimation with Extended Battery Life in Wireless Sensor Networks},\n year = {2018},\n pages = {662-666},\n abstract = {Energy constraint is always a bottleneck in a distributed wireless sensor network (WSN). Online censoring is an effective approach to reduce the overall power consumption by only transmitting statistical informative data. However, individual sensor may still suffer from energy shortage due to frequent transmission of informative data or geographical long distance transmission. In this paper, we consider the parameters estimation problem in WSNs, where the goal is to minimize the estimation error while keeping the network lifetime long. A distributed censoring algorithm is developed, which allows sensor nodes to make autonomous decisions on whether to transmit the sampled data. We show that with the proposed algorithm, the network lifetime extends and approaches to its theoretical limit, and the performance loss in terms of the estimation error is minimal. 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