Cloud Data Synchronization with Limited Bandwidth Communications

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: H92222-18-C-0014
Agency Tracking Number: S2-0369
Amount: $968,908.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: SOCOM163-005
Solicitation Number: 2016.3
Timeline
Solicitation Year: 2016
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-01-31
Award End Date (Contract End Date): 2020-01-30
Small Business Information
162 Genesee Street, Utica, NY, 13502
DUNS: 111305843
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Benjamin Buley
 (315) 732-7385
 buley@brsc.com
Business Contact
 Milissa Benincasa
Phone: (315) 732-7385
Email: benincasa@brsc.com
Research Institution
N/A
Abstract
As the DoD continues to develop applications backed by cloud-based data and enterprise infrastructures, remote-sites will require on-site data caches to permit operation during periods of disconnect from the enterprise.To address this challenge for SOCOMs Chimera system, Black River will develop a stand-alone Chimera system that is independent of Amazon cloud software; develop bi-directional data synchronization capabilities to overcome Disconnected, Intermittent, and Limited (DIL) communication links; and develop graph-based approaches to autonomously identify data of greatest value to Chimera users.Our objective is to provide uninterrupted operation of Chimera at fielded locations, during periods of DIL network connectivity.To further improve operation in austere environments, where user-interaction is limited, we will develop technologies that provide autonomous data prioritization, transfer, and synchronization.The proposed capabilities will benefit scenarios where opportunities and threats have a narrow window of response; e.g., High Value Target engagement, fratricide reduction, and emergency extraction. Our proposed solution is comprised of capabilities that have application to opportunistic prepositioning of data for Internet of Things sensors, autonomous data transfers for power savings in wireless data connections for Remote Controlled Model Aircraft, and encrypted network analysis using wavelet fingerprints to identify ransomware and malware network traffic patterns.

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

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