| Publisher | Indiana University | ||
|---|---|---|---|
| Format | 177.5KB PDF | Date added | 12 Jul 2004 |
| Topics | Data Mining - Analysis, High Performance Computing, Service-Oriented Architecture | ||
| Downloads | 47 | ||
Applications dealing with large data sets obtained via simulation or actual real-time sensor networks are increasing in abundance. The data obtained from real-time sources may contain certain discrepancies which arise from the dynamic nature of the source. Furthermore, certain computations may not require all the data and hence this data must be filtered before it can be processed. By installing adaptive filters that can be controlled in real-time, one can filter out only the relevant parts of the data thereby improving the overall computation speed. This paper presents an architecture that links these distributed filters to achieve high throughput dataflow for real-time streaming and high-performance applications.
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