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Welcome to the Carnegie Mellon University's home-page for the Q-MARS project, which is part of a MURI effort with the University of Illinois at Urbana-Champaign and the University of Virginia at Charlottesville. This MURI effort focuses on QoS Support for Surveillance and Control Systems, and is funded by DARPA and ONR.

In the surveillance and control systems, Quality-of-Service support is increasingly important to provide real-time results under an dynamic environment with uncertainty.  In many applications the relation between level of service and resource requirements is not fixed. Environmental factors outside the control of the system affect this relationship and may also affect the perceived utility for a given level of service. An example of such application is radar tracking.


In order to guarantee optimal timing services with limited resources (including contented resources, limited priority granularity, etc.), the following research problems need to be solved: resource management with environmentally dependent measures of quality, optimization with indirect mapping between QoS and application control, prediction of performance with stochastic tasks, management of heterogeneous resources including both computing and physical resources, development of protocols for QoS control of applications and mechanisms.  We divide the above problems into Q-RAM (QoS-based Resource Allocation in Real-time Distributed System), Quantized Earliest-deadline-first scheduling.  We are implementing these solutions under the framework of Sesco (Session-Coordinator) system.