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Proceedings Paper

The product generation architecture for the GOES-R ground system
Author(s): Gerald Dittberner; Satya Kalluri; Allan Weiner; Michael Blanton; Anderson Tarpley
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Paper Abstract

The GOES-R Ground System (GS) will produce a much larger set of products with higher data density than previous GOES systems. This requires considerably greater compute and memory resources to achieve the necessary latency and availability for these products. Over time, new algorithms could be added and existing ones removed or updated, but the GOES-R GS cannot go down during this time. To meet these GOES-R GS processing needs, the Harris Corporation will implement a Product Generation (PG) infrastructure that is scalable, extensible, extendable, modular and reliable. The primary parts of the PG infrastructure are the Service Based Architecture (SBA) and the Distributed Data Fabric (DDF). The SBA is the middleware that encapsulates and manages science algorithms that generate products. The SBA is divided into three parts, the Executive, which manages and configures the algorithm as a service, the Dispatcher, which provides data to the algorithm, and the Strategy, which determines when the algorithm can execute with the available data. The SBA is a distributed architecture, with services connected to each other over a compute grid and is highly scalable. This plug-and-play architecture allows algorithms to be added, removed, or updated without affecting any other services or software currently running and producing data. Algorithms require product data from other algorithms, so a scalable and reliable messaging is necessary. The SBA uses the DDF to provide this data communication layer between algorithms. The DDF provides an abstract interface over a distributed and persistent multi-layered storage system (memory based caching above disk-based storage) and an event system that allows algorithm services to know when data is available and to get the data that they need to begin processing when they need it. Together, the SBA and the DDF provide a flexible, high performance architecture that can meet the needs of product processing now and as they grow in the future.

Paper Details

Date Published: 26 August 2010
PDF: 6 pages
Proc. SPIE 7813, Remote Sensing System Engineering III, 781305 (26 August 2010); doi: 10.1117/12.859902
Show Author Affiliations
Gerald Dittberner, Harris Corp. (United States)
Satya Kalluri, NOAA/NESDIS (United States)
Allan Weiner, Harris Corp. (United States)
Michael Blanton, Harris Corp. (United States)
Anderson Tarpley, Harris Corp. (United States)


Published in SPIE Proceedings Vol. 7813:
Remote Sensing System Engineering III
Philip E. Ardanuy; Jeffery J. Puschell, Editor(s)

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