Autonomic Performance Assurance for Multi-Processor Supervisory Control

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-13-C-0170
Agency Tracking Number: O2-1372
Amount: $749,995.00
Phase: Phase II
Program: STTR
Awards Year: 2013
Solicitation Year: 2011
Solicitation Topic Code: OSD11-T01
Solicitation Number: 2011.B
Small Business Information
1310 United Heights Suite 105, Colorado Springs, CO, -
DUNS: 131860632
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Michael Hammel
 Principal Engineer
 (719) 388-8582
Business Contact
 Nancy Scally
Title: CEO
Phone: (719) 388-8582
Research Institution
 University of Colorado (UCCS)
 Xiaobo " Zhou
 1420 Austin Bluffs Parkway
Colorado Springs, CO, 80918-
 (719) 255-3493
 Nonprofit college or university
Multi-processor computing systems are growing in capacity and usage. They encompass multiple, distributed implementations as well as heterogeneous, embedded computing architectures. The processing density enabled by such approaches holds promise for unmanned combat air vehicles (UCAVs) with their plethora of mission sensors and command and control processing requirements. However, the software and middleware required to effectively (and efficiently) harness multi-processor computing power is lacking. The team of Colorado Engineering, Inc. (CEI) and the University of Colorado, Colorado Springs (UCCS) proposes to design and develop an autonomic job scheduling system that addresses two areas of concern performance assurance and energy efficiency in distributed embedded multiprocessor systems for UCAVs. The effort will build on the Phase I program by developing a decentralized and scalable control system that supports automated job scheduling, performance assurance, fault tolerance, energy efficiency, and the migration of control (on-demand) into clouds with wireless networks in UCAVs. A prototype system will be tested in high performance embedded systems and cloud environments to validate performance and value. UCCS will draw on its research into autonomic computing, sustainable computing, and cloud computing, while CEI will leverage its experience with distributed, heterogeneous, high performance, multiprocessor embedded computing architectures during the proposed activities.

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

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