Dynamical analysis of clustering-based wireless sensor networks
نویسنده
چکیده
In wireless sensor networks (WSNs), clustering-based algorithms have been proved to be effective techniques to save energy and improve fault tolerance. In this paper, a scale-free evolving model for clustering-based WSNs with exponential growth behavior is presented, in which the nodes arrive as a Poisson process with rate λ. This model takes into account four types of evolving events: selection of cluster-head nodes, preferential attachment of non cluster-head nodes, failure of non cluster-head nodes, transition of non cluster-head nodes. By using continuum theory, the theoretical computing and simulated results show that the size distribution of cluster in this model follows a power law. The scalefree properties revealed in this model display a tempting application foreground.
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