Third International conference on advances in communication, network and computing

Research Article

Dynamic Cooperative Routing (DCR) in Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-35615-5_13,
        author={Sivasankari H. and Leelavathi R. and Shaila K. and Venugopal K.R. and S. Iyengar and L. Patnaik},
        title={Dynamic Cooperative Routing (DCR) in Wireless Sensor Networks},
        proceedings={Third International conference on advances in communication, network and computing},
        proceedings_a={CNC},
        year={2012},
        month={12},
        keywords={Cooperative Routing Energy Efficient Static Sink Mobile Sink Wireless Sensor Networks},
        doi={10.1007/978-3-642-35615-5_13}
    }
    
  • Sivasankari H.
    Leelavathi R.
    Shaila K.
    Venugopal K.R.
    S. Iyengar
    L. Patnaik
    Year: 2012
    Dynamic Cooperative Routing (DCR) in Wireless Sensor Networks
    CNC
    Springer
    DOI: 10.1007/978-3-642-35615-5_13
Sivasankari H.1,*, Leelavathi R.1, Shaila K.1, Venugopal K.R.1, S. Iyengar2, L. Patnaik3
  • 1: University Visvesvaraya College of Engineering, Bangalore University
  • 2: Florida International University
  • 3: Indian Institute of Science
*Contact email: mailtosankari@yahoo.com

Abstract

Wireless Sensor Networks(WSNs) have micro sensors connected in a network with processing capabilities for communications. It is subjected to a set of resource constraints such as battery power, bandwidth and lifetime. The existing cooperative routing is addressed to reduce the energy consumption. We propose Dynamic Cooperative Routing (DCR) to conserve energy and maximization of lifetime with a static and mobile sink. A mathematical model is developed for the best placement of the sink in the deployment to reduce the distance between sources and sink. A comparative study of DCR algorithm with the existing algorithm is obtained for a static and mobile sink. In case of mobile sink, Comparative analysis shows the improvement in lifetime and energy conservation by 70% and 65% respectively over the existing algorithms.