SBIR/STTR Research Award
SBIR Phase I: Application of Infinitesimal Perturbation Analysis over Continuous Flow Models to a High-Performance Content-based Routing Network
Award amount
$98,991Program and phase
SBIR · Phase IAward year
2003Award details
- Awarding agency
- National Science Foundation
- Branch
- Not reported
- Recipient company
- Semandex Networks Inc.
- Proposal award date
- Not reported
- Contract end date
- Not reported
- UEI
- PSRYWARX7BM1
- Solicitation number
- Not reported
- Topic code
- Not reported
Research abstract
This Small Business Innovation Research (SBIR) Phase I project will investigate distributed traffic-management algorithms applied to overlay networks of Semantic Routers constituting a high-speed Semantic Web. Semandex Networks is pioneering new categories of information routers based on eXtensible Markup Language (XML). These routers automatically know where content is and to where to deliver it, dramatically reducing information breaks. A hierarchy of edge and core application-layer routers interconnect for scalable, accurate, and timely information delivery, in a manner that could not otherwise be economically or technically realized. Traffic management in this real-time heterogeneous system presents new challenges that cannot be solved by traditional link-based point-to-point approaches. Specifically, the bandwidths of the underlying links are shared with other layer-3 traffic of unknown characteristics, and outputs from individual virtual ports are aggregated over the outgoing link or links from an individual layer-7 router.
Commercial application for this project is that flow and management issues needed to enhance next generations Internet structures will be tractable therefore reducing downtimes and increasing net performance.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- Discovery: Multimodal Data Archives
- Data-Driven Technology Discovery Methodologies
- Data-Driven Technology Discovery Application
- Video Data to DDMS Cards
- Disambiguation of Entity Association Statements