2nd International ICST Workshop on Advances in Wireless Sensor Networks 2007

Research Article

An Energy Efficiency Scheme Using Local SNR for Clustered Wireless Sensor Networks

  • @INPROCEEDINGS{10.1109/MOBIQ.2007.4451049,
        author={ Qianyu  Ye and Yu Liu and Lin  Zhang and Chan-hyun  Youn},
        title={An Energy Efficiency Scheme Using Local SNR for Clustered Wireless Sensor Networks},
        proceedings={2nd International ICST Workshop on Advances in Wireless Sensor Networks 2007},
        publisher={IEEE},
        proceedings_a={IWASN},
        year={2008},
        month={2},
        keywords={Acoustic sensors  Clustering algorithms  Energy efficiency  Postal services  Power engineering and energy  Routing protocols  Sensor phenomena and characterization  State estimation  Wireless communication  Wireless sensor networks},
        doi={10.1109/MOBIQ.2007.4451049}
    }
    
  • Qianyu Ye
    Yu Liu
    Lin Zhang
    Chan-hyun Youn
    Year: 2008
    An Energy Efficiency Scheme Using Local SNR for Clustered Wireless Sensor Networks
    IWASN
    IEEE
    DOI: 10.1109/MOBIQ.2007.4451049
Qianyu Ye1,*, Yu Liu1,*, Lin Zhang1,*, Chan-hyun Youn2,*
  • 1: School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China
  • 2: Information and Communications University, Republic of Korea
*Contact email: iceburgue@gmail.com, liuyurainy@163.com, zhanglin@bupt.edu.cn, chyoun@icu.ac.kr

Abstract

In this paper, a local SNR aided sensor selecting (LSAS) algorithm is proposed to meet the energy efficiency requirement of wireless sensor networks (WSNs). In the conventional cluster routing protocols, during each round, all the subordinate sensors need to send their sensed information to their cluster heads, which is energy consuming. Realizing that it is not necessary to involve all the sensors due to the redundancy characteristic of the information on them, we propose that only those sensors with higher local SNR are selected to transmit their sensed data. Experimental results demonstrate that it is sufficient to only use the information on nodes with higher local SNR for target state estimation. The simulations also suggest that the proposed method consumes about 30%-50% less energy than the conventional method