SBIR-STTR Award

Automated Processing, Exploitation and Dissemination
Award last edited on: 8/1/2019

Sponsored Program
SBIR
Awarding Agency
DOD : SOCOM
Total Award Amount
$1,249,758
Award Phase
2
Solicitation Topic Code
SOCOM18-001
Principal Investigator
Joshua Madden

Company Information

Parry Labs LLC

9150 Rumsey Road Suite A6
Columbia, MD 21045
   (571) 420-8313
   N/A
   www.parrylabs.com
Location: Single
Congr. District: 03
County: Howard

Phase I

Contract Number: H9240518P0013
Start Date: 6/29/2018    Completed: 12/31/2018
Phase I year
2018
Phase I Amount
$140,423
Parry Labs proposes the research and development of a distributed, scalable, heterogeneous system to perform automated Processing, Exploitation, and Dissemination (PED) of data feeds.The proposed system will run as a distributed cluster that employs Server-less function execution and Containers to enable the reliable, scalable running of applications. The cluster will employ a peer-to-peer overlay network that incorporates aspects of both Software Defined Networking (SDN) and Delay/Disruption Tolerant Networking (DTN). The proposed system will reduce the human workloads both for analyzing and requesting data feeds by automating the workflow. The PED cycle time will be reduced by automated the collection, ingest, processing, and generation of data feeds. On order, data feeds not requiring human intervention will be automatically processed and disseminated. Data feeds requiring additional human analysis can be flagged for review and update by an analyst. Workflows will include options for generating metrics, setting alerts, and managing subscribers for data feeds. Workflow curators will select from one or more data feeds, specify filter criteria, select additional processing, and specify the type of output.

Phase II

Contract Number: H9240519C0017
Start Date: 4/17/2019    Completed: 4/17/2020
Phase II year
2019
Phase II Amount
$1,109,335
Parry Labs proposes the continued development of a distributed, scalable, heterogeneous system to perform Automated Processing, Exploitation, and Dissemination (APED) of multi-INT sensor feeds. The system will run as a distributed cluster that employs Serverless function execution and containers to enable the reliable, scalable running of applications. The cluster will employ a peer-to-peer overlay network that incorporates aspects of both Software Defined Networking (SDN) and Delay/Disruption Tolerant Networking (DTN). The system will reduce the human workloads both for analyzing and requesting data feeds by automating the workflow via machine learning algorithms. The PED cycle time will be reduced by automated the collection, ingest, processing, and generation of data feeds. On order, data feeds not requiring human intervention will be automatically processed and disseminated. Data feeds requiring additional human analysis can be flagged for review and update by an analyst. Workflows will include options for generating metrics, setting alerts, and managing subscribers for data feeds. Workflow curators will select from one or more data feeds, specify filter criteria, select additional processing, and specify the type of output.