This text proposes a model-based approach to the design and implementation of Computational Sensor Networks (CSNs). It is a high-level paradigm that provides a strong scientific computing foundation, as well as the basis for robust software engineering.

Describes a computational framework for sensor networks Discusses how CSNs can be used to develop models to determine the unknown aspects of particular measurement systems given a state of the physical phenomena Discusses how computational sensor networks can be used to model sensor network systems of any sort, including surveillance, environment modeling, structure monitoring, and biomedical monitoring, as well as in the large to dynamic data driven large-scale simulation scenarios

Inhalt
CSN: Overview of Approach.- Leadership Algorithms.- Coordinate Frames and Gradient Calculation.- Pattern Formation in S-Nets.- Logical Sensors and Computational Mapping.- Mobile Robot Performance Analysis.- CSN: The Heat Equation.- Bayesian Estimation of Distributed Phenomena.