Autonomic Performance Assurance for Multi-Processor Supervisory Control

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 develop an autonomic performance assurance framework and associated techniques that support automated job scheduling and guarantee performance for multi-processor supervisory control. Through the development, verification, and validation of the proposed framework, the project will increase the autonomy and capability of unmanned combat air vehicles (UCAV). Autonomic performance control is crucial to computer controls in military operations with highly dynamic constraints and topologies. However, it is significantly challenging because the performance is the result of a complex interaction of complex workloads in a complex underlying computer system. UCCS will draw on its research into autonomic computing while CEI will leverage its experience with distributed/grid computing and heterogeneous, high performance, multi-processor embedded computing architectures for UCAVs to guide the proposed activities.