Stack-based scheduling for realtime processes
Real-Time Systems
Improvement in feasibility testing for real-time tasks
Real-Time Systems
An Optimal Algorithm for Scheduling Soft Aperiodic Tasks in Dynamic-Priority Preemptive Systems
IEEE Transactions on Software Engineering
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Priority Inheritance Protocols: An Approach to Real-Time Synchronization
IEEE Transactions on Computers
Task Period Selection and Schedulability in Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Jitter Compensation for Real-Time Control Systems
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
FUNDAMENTAL DESIGN PROBLEMS OF DISTRIBUTED SYSTEMS FOR THE HARD-REAL-TIME ENVIRONMENT
FUNDAMENTAL DESIGN PROBLEMS OF DISTRIBUTED SYSTEMS FOR THE HARD-REAL-TIME ENVIRONMENT
Minimum Deadline Calculation for Periodic Real-Time Tasks in Dynamic Priority Systems
IEEE Transactions on Computers
A real-time framework for multiprocessor platforms using Ada 2012
Ada-Europe'11 Proceedings of the 16th Ada-Europe international conference on Reliable software technologies
Embedded Systems Design
Adding multiprocessor and mode change support to the Ada real-time framework
ACM SIGAda Ada Letters
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Industrial control applications are usually developed in two phases: control design and real-time system implementation. In the control design stage a regulator is obtained and later it is translated into an algorithm in the implementation phase. Traditionally, these two phases have been developed in separate ways. Recently, some works have pointed out the necessity of the integration of the control design and its implementation. One of these works reduce the delay variance of control tasks (defined as the control action interval (CAI) and data acquisition interval (DAI) parameters) splitting every task into three parts. The CAI reduction method highly reduces the delay variance and improves the control performance. This work shows how to evaluate these delays under static and dynamic scheduling policies. A new task model is proposed in order to reduce the CAI and DAI parameters, which implies an improvement in the control performance. The new task model will be implemented in a real process, and the experimental measurements will show how, effectively, the control performance is highly improved with the methods presented in this paper.