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 re-attempts before concluding there is no node in the forwarding region. All expressions involving multi-dimensional integrals are derived and evaluated readily with quasi-Monte Carlo integration methods. An importance sampling function is derived to speed up the quasi-Monte Carlo methods. The integral expressions are compa...
Holger Paul Keeler, Peter G. Taylor