This dissertation considers two important topics related to advancing wireless sensor network (WSN) technology: the privacy concerns raised by ever increasing collection personally identifying data by sensing systems, and the opportunities for synergetic function created by imbuing sensor platforms with mobility. On the privacy side, the dissertation focuses on the collection of power consumption data in current and future demand-response systems. We build a data-gathering and behavior extraction system and conduct a small-scale monitoring experiment on a private residence. Our results show that certain personal information may be estimated with a high degree of accuracy. On the mobility side, we consider two difficult problems in multi-agent coordination: the Multiple Path Consensus (MPC) problem, and the Multiple Sensing Region Field of Interest (MSRF) problem. We characterize both problems as NP-complete, then proceed to develop computationally tractable formulations for each. We then develop algorithms which are able to solve practically-sized instances of these problems to optimality. Finally, we develop a practical real-world platform upon which to test multi-agent coordination algorithms, and give an example "iteratively-deployed WSN" application.