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| Content Provider | Springer Nature Link |
|---|---|
| Author | Goossens, Joël Grolleau, Emmanuel Cucu Grosjean, Liliana |
| Copyright Year | 2016 |
| Abstract | This paper gives and proves correct a simulation interval for any schedule generated by a deterministic and memoryless scheduler (i.e., one where the scheduling decision is the same and unique for any two identical system states) for identical multiprocessor platforms. We first consider independent periodic tasks, then generalize the simulation interval to tasks sharing critical resources, and subject to precedence constraints or self-suspension. The simulation interval is based only on the periods, release times and deadlines, and is independent from any other parameters. It is proved large enough to cover any feasible schedule produced by any deterministic and memoryless scheduler on multiprocessor platforms, including non conservative schedulers. To the best of our knowledge, this simulation interval covers the largest class of task systems and scheduling algorithms on identical multiprocessor platforms ever studied. This simulation interval is used to derive a simulation algorithm using a linear space complexity. Finally, a generic exact schedulability test based on simulation is presented. This test can be applied only when sustainability is consistent with online variability of the tasks’ parameters. |
| Starting Page | 808 |
| Ending Page | 832 |
| Page Count | 25 |
| File Format | |
| ISSN | 09226443 |
| Journal | Real-Time Systems |
| Volume Number | 52 |
| Issue Number | 6 |
| e-ISSN | 15731383 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2016-06-27 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Real-time scheduling Simulation intervals Multiprocessor Computer Systems Organization and Communication Networks Communications Engineering, Networks Special Purpose and Application-Based Systems Performance and Reliability Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Computer Networks and Communications Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications Modeling and Simulation |
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