RBNB buffers streaming data modules across network layers.

In 1995 Creare engineers were working on a wavelet analysis project to detect wing vibration for NASA Dryden Flight Research Center, connecting the data acquisition sensors on aircraft wings to data analysis software. For a demonstration of the system at Dryden, our research colleague at NASA asked if we could hook into their network, so we customized networking technology from a previous project to oblige his request. Imagine our surprise when he announced over the public address system that for the first time ever, NASA had an important category of live test data streaming into the control room.

In fact, the need for networked distribution of streaming data is continually increasing. At Creare, we developed our data distribution software into Ring-Buffered Network Bus® (RBNB), a middleware system that merges data acquisition, data monitoring, and data distribution into a network scalable topology. The middleware acts as both a universal sink and a universal source, providing multiple simultaneous users network access to real-time test and analysis data at a speed of over 10MB/sec and over 1000 frames/sec using standard PC computers. In 2000, RBNB was honored as one of the most technologically significant innovations of the year with an R&D 100 Award.

Part of RBNB’s innovation lies in its use of a Web-based infrastructure for data distribution and part lies in the method used for data management. Traditionally, data acquisition and distribution take place in real-time, while monitoring takes place in non-real-time. Shifting to non-real-time prior to distribution reduces costs and performance requirements. To make the system widely accessible, as well as platform- and application-independent, we used a standard Internet Protocol (IP) computer network as a non-real-time data distribution system. RBNB V3.0 is now released under an Apache 2.0 Open Source License.

Furthermore, RBNB makes a break from the historic division between static and streaming data. RBNB treats both forms of data as functionally equivalent; to RBNB, streaming data is a sequence of static data frames, and static data is a time-slice of a data stream. This approach makes it easy to manipulate data, especially time-referenced information.

We recently worked on a program for the Homeland Security Department using RBNB to increase the efficient use of 3-D surveillance imagery. Our technology integrates middleware data distribution infrastructure and 3-D map technology. By panning the view and sliding a “time throttle,” the operator can efficiently and intuitively search and select data, tracking both back and forth in time and across space.

RBNB is currently used by scientists on a wide range of projects, such as the NASA African Monsoon Multidisciplinary Analysis campaign, tropical cloud system observations in Costa Rica, and a planned mission to search the Antarctic coast for Emperor penguins. In the U.S., scientists at U.C. San Diego’s supercomputing group use RBNB to share data for earthquake simulations, and the National Oceanic and Atmospheric Administration uses it for hurricane monitoring. It has been a fascinating process to expand, refine, and advance our RBNB program for a tremendous range of projects.

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