Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks

This paper describes two novel techniques, information-driven sensor querying (IDSQ) and constrained anisotropic diffusion routing (CADR), for energy-efficient data querying and routing in ad hoc sensor networks for a range of collaborative signal processing tasks. The key idea is to introduce an information utility measure to select which sensors to query and to dynamically guide data routing. This allows us to maximize information gain while minimizing detection latency and bandwidth consumption for tasks such as localization and tracking. Our simulation results have demonstrated that the information-driven querying and routing techniques are more energy efficient, have lower detection latency, and provide anytime algorithms to mitigate risks of link/node failures.