1st International ICST Workshop on Performance Methodologies and Tools for Wireless Sensor Networks

Research Article

From Rosenstock model to random walk based routing in wireless sensor networks

  • @INPROCEEDINGS{10.4108/ICST.VALUETOOLS2009.7814,
        author={Issam  Mabrouki and Xavier  Lagrange},
        title={From Rosenstock model to random walk based routing in wireless sensor networks},
        proceedings={1st International ICST Workshop on Performance Methodologies and Tools for Wireless Sensor Networks},
        publisher={ACM},
        proceedings_a={WSNPERF},
        year={2010},
        month={5},
        keywords={Wireless sensor networks Routing Random walk Performance evaluation},
        doi={10.4108/ICST.VALUETOOLS2009.7814}
    }
    
  • Issam Mabrouki
    Xavier Lagrange
    Year: 2010
    From Rosenstock model to random walk based routing in wireless sensor networks
    WSNPERF
    ICST
    DOI: 10.4108/ICST.VALUETOOLS2009.7814
Issam Mabrouki1,*, Xavier Lagrange2,*
  • 1: LIA/CERI, University of Avignon, Agroparc, BP 1228, 84911, Avignon, France.
  • 2: Institut TELECOM/TELECOM Bretagne, Campus de Rennes, France.
*Contact email: issam.mabrouki@univ-avignon.fr, xavier.lagrange@telecom-bretagne.eu

Abstract

In this paper, we investigate random walk based routing in wireless sensor networks (WSN) that contains sink nodes independently distributed at random. Our goal is to quantify the effectiveness of such techniques based on the derivation of closed-form expressions. In particular, we focus on the global delay taken for the random walk to deliver data packets from sensor to sink nodes and study its statistics through closed-form derivations. At low concentration of sink nodes, we analytically establish an approximate formula that provides the cumulative distribution function of the global delay. We also perform a series of simulations to validate the analytical results. These simulation studies clearly agree with the analytical results provided that the concentration of sink nodes remains small. The main result of this paper is that the performance of data gathering based on random walks in randomized deployment can be significantly enhanced if the concentration of sink nodes is well tuned.