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Resilient Execution of Localized Algorithms at the Tactical Edge (RELATE)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-20-P-0025
Agency Tracking Number: A19C-004-0029
Amount: $166,476.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A19C-T004
Solicitation Number: 19.C
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-02-27
Award End Date (Contract End Date): 2020-05-31
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Curt Wu
 Chief Software Engineer
 (617) 491-3474
 cwu@cra.com
Business Contact
 Yvonne Fuller
Phone: (617) 491-3474
Email: yfuller@cra.com
Research Institution
 Boston University
 Ms. Diane Baldwin Ms. Diane Baldwin
 
25 Buick Street
Boston, MA 02215
United States

 (617) 353-4365
 Nonprofit College or University
Abstract

Warfighters engaged in tactical operations are increasingly reliant on time-sensitive sensor information collected from Internet of Battlefield Things (IoBT) devices at the tactical edge to achieve mission goals. If the information flow is disrupted or the information is not processed correctly, then mission success can be severely impacted. A tactical edge network poses unique challenges for information collection because of its limited connectivity between information producers and consumers, its limited computing resources, its highly dynamic nature, and its exposure to both environmental and malicious factors that disrupt transmission and processing. To enable Warfighters to process information using computational resources at the tactical edge, we propose a framework for Resilient Execution of Localized Algorithms at the Tactical Edge (RELATE). RELATE is based on a hierarchical networking architecture and a dynamic self-organizing structured overlay network to enable discovery and allocation of computational and communication resources across a rapidly changing network. RELATE optimizes the use of available network and computational resources to increase both the timeliness of and the confidence in the results of distributed algorithms executing in tactical edge networks.

* Information listed above is at the time of submission. *

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