Topology of Sensor Networks in Distributed Detection

We study the topology of sensor networks. With parallel architectures, the design is trivial - sensors forward their local decisions to a global fusion center. With web architectures, sensors communicate only with ´neighbors´ and evolve their local decisions to reach a ´consensus.´ In practice, it is important to reach a consensus with minimal communications and processing cost. The convergence rate of the consensus algorithm depends on 1) the weights assigned to the network links; and 2) the connectivity pattern of the network. We apply concepts from small world networks to design the topology and the weights when the local decisions are quantized and study the impact on network performance when we trade number of links for number of bits per decision