Real-time dbms for data fusion

Abstract

As data and information fusion technology and application evolves, the need is increasing to cope with large amounts and diverse types of data. Although there would be many benefits to employment of Data Base Management Systems (DBMS) in automated fusion processes the data access throughput requirements of automated fusion processes have vastly exceeded the performance of off-the-shelf DBMS's. The availability of large random access memories is allowing the development of real-time data base management systems. While these are currently being used in financial market and telecommunications applications, their ability to bring DBMS benefits to data fusion applications has yet to be explored. This paper presents results of experimentation with these emergent real-time DBMS's for automated fusion applications. We used algorithms, data characteristics, and scenarios from deployed and R&D systems. The applications-dependent data structures were converted to Entity-Relationship models and generated into real-time and conventional DBMS's.