Enabling distributed radar data retrieval and processing in distributed collaborative adaptive sensing environments

This thesis describes the integration of radar network and grid computing technologies to provide a set of grid services to manipulate and store data from different radars, to execute algorithms on different platforms in a transparent way to end users, and to provide secure access to storage systems and instruments. The solution approach considered is a grid-based system which includes a Grid Portal Interface, a distributed storage to radar data management, and Grid services implementing distributed algorithms to process data radar information.; A major requirement of this system is data availability and reliability. Consequently, have been implemented two redundancy schemes to perform the data management of the network: A simple Replication Algorithm and the Information Dispersal Algorithm (IDA). Experimental results show that IDA provides better reliability and less storage spending than the traditional replication algorithm. Furthermore, under the same conditions, the redundancy in the replication technique is three times or more than IDA, when the reliability required is over 90%. IDA is normally used to perform security deployments where message encryption is required. Thus, this algorithm has been modified to enable large file management in order to satisfy the large amount of data generated by radars.