Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers

Research Article

A Stable Energy-Efficient Location Based Clustering Scheme for Ad Hoc Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-37949-9_7,
        author={Anubhuti Mohindra and Charu Kumar},
        title={A Stable Energy-Efficient Location Based Clustering Scheme for Ad Hoc Networks},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers},
        proceedings_a={QSHINE},
        year={2013},
        month={7},
        keywords={Clustering Mobile Ad Hoc network (MANET) Stability Location Services GPS Energy Conservation ELS},
        doi={10.1007/978-3-642-37949-9_7}
    }
    
  • Anubhuti Mohindra
    Charu Kumar
    Year: 2013
    A Stable Energy-Efficient Location Based Clustering Scheme for Ad Hoc Networks
    QSHINE
    Springer
    DOI: 10.1007/978-3-642-37949-9_7
Anubhuti Mohindra1,*, Charu Kumar1,*
  • 1: Jaypee Institute of Information Technology
*Contact email: anubhuti.mohindra@jiit.co.in, charu.kumar@jiit.co.in

Abstract

             is an approach applied in mobile ad hoc networks to organize the hosts in groups called . The paper focuses on implementing a Clustering technique that conserves , provides  and keeps the and using  by setting for different parameters in dynamic ad hoc environment of uncontrolled movement of nodes, low bandwidth of wireless channel and energy limited nodes. The mechanism uses pools of Primary and Secondary cluster heads (CHs) to provide uninterrupted communication due to node mobility. The protocol saves network resources by reducing the information exchange amongst the nodes and limiting it to clusters and CHs. The paper includes a case that models different scenarios based on the proposed protocol. Also, characteristic analysis of our clustering scheme with some of the existing algorithms is done which shows the strength of this scheme over others.