Dynamic Resource Management for a Sensor-Fusion Application via Distributed Parallel Grid Computing

Sensor data fusion applications generally use networked computational resources to process information. For high sensor data rates, distributed, parallel computing is necessary to keep up with the processing of the incoming signals, and the dynamic management of these geographically dispersed resources is necessary for fault tolerance and efficient use of resources. This research reports on a proof of concept project and demonstration in which a high data-rate sensor fusion application was deployed on a distributed, parallel, dynamic “grid” network of computers.