Distributed sensor networks (DSNs) are composed of numerous small, low-cost, randomly located nodes. The network can be scalable to thousands of nodes that cooperatively perform complex tasks such as intelligent measurement. The network must be able to self-organize, adapt to random node spacing, execute algorithms for signal processing, and operate as power efficiently as possible. The major applications of DSNs are for monitoring environmental conditions, tracking the movements of birds and small animals, monitoring product quality, and building automation and defense networks. Smart Dust is a term recently coined at the University of California, Berkeley, to describe massively distributed sensor networks consisting of cubic-millimeter sized motes [1, 2]. The small size and anticipated low cost of the motes will help to collect information cost-effectively and less intrusively.