2014 # A stochastic process model of the hop count distribution in wireless sensor networks

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“…Hop counts generated by this model are referred to as independent, empirical hop counts, M3: observations are independent draws from the translated Poisson model (2), and are referred to as idealized, model-generated hop counts. It was shown through simulations of the generative models M1 and M3 in [6], that the smallest average target localization error is achieved using hop count observations generated by M3. In [6], observations are taken at randomly selected nodes of the WSN.…”

confidence: 99%

“…Hop counts generated by this model are referred to as independent, empirical hop counts, M3: observations are independent draws from the translated Poisson model (2), and are referred to as idealized, model-generated hop counts. It was shown through simulations of the generative models M1 and M3 in [6], that the smallest average target localization error is achieved using hop count observations generated by M3. In [6], observations are taken at randomly selected nodes of the WSN.…”

confidence: 99%

“…In [6], it was established that for networks with strongly supercritical mean node degree δ, the hop count at distance r from the target is well approximated by a translated Poisson distribution,…”

confidence: 99%