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Dissemination of weather intelligence information and met sensor data acquisition using Jini/JavaSpaces technologies

Digitization of the battlespace for current and future combat systems cannot be complete without effective weather intelligence products and decision aids. An important challenge facing current weather intelligence products involves the simultaneous collection and dissemination of the vast amounts of raw and processed meteorological data. Data can originate from various types of sensors, sources, and computing models. Also, data collections can be sporadic and their publication can materialize on an assortment of formats and through dissimilar channels. To resolve many of these challenges, we have investigated a tuple-spaces solution that provides lose-coupling of sensors, systems, and weather forecasting models in a networked environment. Of interest are the results of experiments that employ the Jini/JavaSpaces implementation to resolve the problems of data acquisition and dissemination. This paper will present our space-based design to loosely-couple several weather sensors and simultaneously acquire their data at high output rates. Our results show that tuple-spaces implementations simplify acquisition and distribution of weather intelligence information. Other experimental results will demonstrate that a space-based architecture can also be employed by other network centric systems that involve information dissemination, decision aids, and collaboration/computing environments.