Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Robust aperiodic scheduling under dynamic priority systems
RTSS '95 Proceedings of the 16th IEEE Real-Time Systems Symposium
On task schedulability in real-time control systems
RTSS '96 Proceedings of the 17th IEEE Real-Time Systems Symposium
Elastic Task Model for Adaptive Rate Control
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Integrating Multimedia Applications in Hard Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Design and Evaluation of a Feedback Control EDF Scheduling Algorithm
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Handling Execution Overruns in Hard Real-Time Control Systems
IEEE Transactions on Computers
Efficient Reclaiming in Reservation-Based Real-Time Systems with Variable Execution Times
IEEE Transactions on Computers
Quality-of-Control Management in Overloaded Real-Time Systems
IEEE Transactions on Computers
Control-scheduling codesign of real-time systems: The control server approach
Journal of Embedded Computing - Real-Time Systems (Euromicro RTS-03)
On self-triggered full-information H-infinity controllers
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Real-time control system analysis: an integrated approach
RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
Capacity sharing for overrun control
RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
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In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras has become a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In such environments, control tasks have a normally short computation time but also an occasional long computation time; therefore, the use of worst-case execution time is inefficient for controlling performance optimization. Nevertheless, to maintain the control stability, we still ned to guarantee the task set even if the worst case arises. In this paper, we propose an integrated approach to control performance optimization and task scheduling for control applications where the execution time of each task can vary greatly. We create an innovative approach to elastic control that allows us to fully utilize the processor to optimize the control performance and yet guarantee the schedulability of all tasks under worst-case conditions.