SBIR/STTR Research Award

Command and Control of Dynamic Traffic Prioritization (C2DTP) to Enable Mission-Responsive Crypto-Partitioned Networks

Award identifier cd112a87ab6419ca1867f65fed881310fb6b6219ec5120087f090a6e480d3a87Awarding agency Department of Defense · Air Force

Award amount

$149,367

Program and phase

SBIR · Phase I

Award year

2014

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
PROGENY SYSTEMS, LLC
Proposal award date
2014-06-24
Contract end date
2015-03-23
UEI
MU3CM1145E44
Solicitation number
2014.1
Topic code
AF141-049

Research abstract

ABSTRACT: Today"s data prioritization structures are designed to meet the needs of the mission as well as the technology permits a single"stack"of priorities is implemented and used to evaluate traffic relative to its competitors in the queue. But the missions of today"s Air Force continue to broaden including such disparate activities as traditional air supremacy, intelligence collection, humanitarian operations, missile defense, and others. Each mission is likely to place different emphasis on data of different types to best convey the information most relevant to mission success. Just as critically, the determination of the relevance of a particular piece of information to the mission may be dependent on details of the data itself, rather than simply the transport, protocol, source, or destination. For example, while contact reports are important, a contact reported outside the area of operations may be less important than for a contact approaching the force. Today"s prioritization rules are stratified by priorities whose granularity permits only comparisons between data types, and not their contents. A more flexible and capable system is needed to permit more intelligent and mission-oriented prioritization of data on Air Force networks. BENEFIT: The approach described in this proposal can be adapted to any dynamic network, either at a system/subsystem level or at an asset level. Regardless of the implementation point, it is supported by a coordinated multi-node management framework that can be applied to many disparate situations or network types. Examples of organizations that could apply a managed bandwidth allocation and prioritization tool include any location served by a limited bandwidth that aggregates data from multiple input sources. This includes aircraft communication systems, unmanned systems, shipboard radio rooms, and headquarters communications sites. The approach we are proposing is tailored to military systems due to the promulgation model for information priority profiles: this structure for command by a designated authority pervades the military, including autonomous or unmanned systems. Therefore we believe that for any case where an information exchange node is not guaranteed to be adequately serviced by its available communications resources, if there is a command and control (C2) structure in place, the approach described in this proposal could be applied with additional consideration only for the specific information types and integration with the targeted hardware and software environment. Possible applications focusing on a simple-to-use GUI to select data prioritization needs based on operator preference or predefined rule sets could be leveraged within several commercial ventures. VPNs depend on tunneling protocols that encrypt data at the sending end and decrypt at the receiving end, so having the benefit of prioritizing this data before encryption could increase the overall network throughput and reduce network latency. A CAD worker who uses a VPN to connect to his company"s internal network could set up a rule set to give a higher priority to CAD updates as opposed to emails and voice mail. A gaming network could also use a rule set to make reports about hacking attempts its highest priority. Additionally the flexibility of the GUI allows these rule sets to be changed when conditions change. Dynamic prioritization allows a user to adjust prioritization based on current or upcoming conditions. Just this feature along would be of great interest to many commercial endeavors.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

301 SBIR/STTR records share this UEI (1996–2020). Reported award amounts total $149,466,550. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Homeland Security, National Aeronautics and Space Administration, Department of Transportation

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.