Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

Here is a coherent approach to sensor network scheduling for parameter estimation in dynamic distributed systems modeled with partial differential equations, applying the so-called Fisher information matrix to the covariance matrix of parameter estimates.

Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment.

Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed algorithms, and the numerical examples to be invaluable.

Presents a comprehensive treatment of sensor scheduling problems in the context of sensor networks Demonstrates many original solutions dedicated to the networks with scanning and mobile sensor nodes Offers numerous effective algorithms for sensor scheduling and trajectory planning Contains various numerical examples related to engineering applications

Inhalt
Introduction.- Experimental design in sensor scheduling.- Sensor activation for scanning networks.- Resource aware mobile sensor routing.- Decentralized sensor scheduling using randomized gossip algorithms.- Combinatorial approach to sensor activation.- Sensor location under parametric and location uncertainty.- Sensor network design for fault diagnosis in DPSs.- Extensions toward challenging problems of network scheduling.- Conclusions and further research directions.