A Model Framework for Greedy Routing in a Sensor Network with a Stochastic Power Scheme

A stochastic model is formulated and analyzed to study the advancements of messages under greedy routing in a sensor network with a power- saving scheme. The aim of this model is give a better understanding of stochastic dependencies arising in the system and to offer a method of computing the advancement of message under greedy routing. We observe that the majority of the stochastic dependence from a routing path is captured by including only the previous forwarding node location. We examine a simple uncoordinated power- saving scheme with a new understanding of its effects on local node density. We propose a method for sensibly limiting the number of transmission reattempts before concluding there is no node in the forwarding region. All expressions involving multidimensional integrals are derived and evaluated readily with quasiMonte Carlo integration methods. An importance sampling function is derived to speed up the quasi- Monte Carlo methods. The integral expressions are compared to simulations and give very agreeable results.