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| Content Provider | Springer Nature Link |
|---|---|
| Author | Lee, Sheayun Min, Sang Lyul Kim, Chong Sang Lee, Chang Gun Lee, Minsuk |
| Copyright Year | 1999 |
| Abstract | In multi-tasking real-time systems, inter-task cache interference due to preemptions degrades schedulability as well as performance. To address this problem, we propose a novel scheduling scheme, called limited preemptive scheduling (LPS), that limits preemptions to execution points with small cache-related preemption costs. Limiting preemptions decreases the cache-related preemption costs of tasks but increases blocking delay of higher priority tasks. The proposed scheme makes an optimal trade-off between these two factors to maximize the schedulability of a given task set while minimizing cache-related preemption delay of tasks. Experimental results show that the LPS scheme improves the maximum schedulable utilization by up to 40\% compared with the traditional fully preemptive scheduling (FPS) scheme. The results also show that up to 20\% of processor time is saved by the LPS scheme due to reduction in the cache-related preemption costs. Finally, the results show that both the improvement of schedulability and the saving of processor time by the LPS scheme increase as the speed gap between the processor and main memory widens. |
| Starting Page | 257 |
| Ending Page | 282 |
| Page Count | 26 |
| File Format | |
| ISSN | 09226443 |
| Journal | Real-Time Systems |
| Volume Number | 17 |
| Issue Number | 2-3 |
| e-ISSN | 15731383 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 1999-01-01 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Processor Architectures Special Purpose and Application-Based Systems Operating Systems Computing Methodologies |
| 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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