Data Compression for Bandwidth Constrained Environments Navy SBIR FY2012.1 Sol No.: Navy SBIR FY2012.1 Topic No.: N121-052 Topic Title: Data Compression for Bandwidth Constrained Environments Proposal No.: N121-052-0557 Firm: Object Computing Inc. 12140 Woodcrest Executive Drive Suite 250 St. Louis, Missouri 63141-5099 Contact: Marc Neeley Phone: (314) 590-0259 Web Site: www.ociweb.com Abstract: We propose to extend existing free and open source software to construct a framework solution which implements a multi stage process to support the SBIR requirements. The baseline approach includes an encoding stage followed by a compression stage with optional encryption and transmission stages. Our approach referred to as "Framework for Rule-based Encoding and Stream COmpression (FRESCO)" leverages proven techniques developed for the finance industry to support high volume market data in a low latency manner. FRESCO's first stage analyzes source data and encodes it for the purpose of reducing redundant content and preparing it for optimal compression. Rules written in XML govern encoding behavior and are configuration managed to support data life-cycle. Rules are loaded and interpreted at runtime removing the need to modify encoding software. Automated tools analyze representative source data to assist in development of encoding rules. The second stage is responsible for receiving content from the encoding stage and selecting an appropriate best-of-breed compression algorithm optimized for the encoded data. FRESCO will accommodate pluggable compression components to achieve greater product flexibility. Preliminary testing with candidate data shows we are able to exceed the goal of 1100:1 compression. Benefits: This open source, rule-based framework, that we are proposing offers a general way to combine domain specific encoding with general purpose, but appropriate compression techniques that are consistent with a wide variety of types of information. Not just system health information but many other types. Other Commands and industries that depend on high speed data transmission, in demanding circumstances, such as unmanned air systems, pharmacy fulfillment systems, have indicated interest in this version synchronized approach to reducing high volume transmissions. Return