We describe basic properties of Markov chains on finite state spaces and their application to Green functions, partial differential equations, and their (approximate) solution using random walks on a graph. Attention is paid to the influence of boundary conditions (Dirichlet/von Neumann). We apply these ideas to the study of traffic propagation and distribution in ad hoc networks.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)