Introduction to algorithms
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Probabilistic performance guarantee for real-time tasks with varying computation times
RTAS '95 Proceedings of the Real-Time Technology and Applications Symposium
Statistical Rate Monotonic Scheduling
Statistical Rate Monotonic Scheduling
Stochastic Analysis of a Reseveration Based System
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Specification, Implementation, and Validation of Object-Oriented Embedded Systems
ECOOP '00 Proceedings of the Workshops, Panels, and Posters on Object-Oriented Technology
ACM Transactions on Embedded Computing Systems (TECS)
Toward probabilistic real-time calculus
ACM SIGBED Review
Embedded Systems Design
Embedded Systems Design
Efficient and robust probabilistic guarantees for real-time tasks
Journal of Systems and Software
Re-sampling for statistical timing analysis of real-time systems
Proceedings of the 20th International Conference on Real-Time and Network Systems
PROARTIS: Probabilistically Analyzable Real-Time Systems
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on Probabilistic Embedded Computing
Challenges and new trends in probabilistic timing analysis
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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Traditionally, real-time systems require that the deadlines of all jobs be met. For many applications, however, this is an overly stringent requirement. An occasional missed deadline may cause decreased performance but is nevertheless acceptable. We present an analysis technique by which a lower bound on the percentage of deadlines that a periodic task meets is determined and compare the lower bound with simulation results for an example system. We have implemented the technique in the PERTS real-time system prototyping environment [6, 7].