Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
—This paper addresses the dynamics of broadcast flooding in random wireless ad hoc networks. In particular, we study the subset of nodes covered by a flood as well as timing is...
We study the sensitivity of equilibria in the well-known game theoretic traffic model due to Wardrop. We mostly consider single-commodity networks. Suppose, given a unit demand fl...
We study network capacity limits and optimal routing algorithms for regular sensor networks, namely, square and torus grid sensor networks, in both, the static case (no node failu...
It is common practice in wireless multihop network evaluations to ignore interfering signals below a certain signal strength threshold. This paper investigates the thesis that thi...
Douglas M. Blough, Claudia Canali, Giovanni Resta,...