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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei, T. Mishra, P. Wu, K. Liang, H. |
| Copyright Year | 1990 |
| Abstract | Energy-efficient task allocation and scheduling schemes with deterministic fault-tolerance capabilities are proposed for symmetric multiprocessor systems executing tasks with hard real-time constraints. The proposed heuristic is proven to achieve energy savings by optimally balancing application workload among processors in a system. Based on the observation that fault-free operation is expected to remain dominant in the near future and the probability of the worst case faults is low, an optimistic fault-tolerant heuristic is then proposed to achieve maximum energy savings in the absence of faults while degrading gradually to meet application timing requirements in the worst case of faults. Simulation results show that compared to state-of-art allocation and scheduling schemes proposed heuristic achieves average energy savings of up to 70%. It is also shown that optimistic approach is more resilient to variations in application utilizations and fault occurrences beyond system specifications. |
| Sponsorship | IEEE Computer Society |
| Starting Page | 1511 |
| Ending Page | 1526 |
| Page Count | 16 |
| File Size | 3979681 |
| File Format | |
| ISSN | 10459219 |
| Volume Number | 19 |
| Issue Number | 11 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-11-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Energy efficiency Fault tolerant systems Real time systems Multiprocessing systems Circuit faults Processor scheduling Embedded system Parallel processing Checkpointing Fault tolerance Scheduling and task partitioning Energy-aware systems Real-time and embedded systems Multiprocessor Systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Computational Theory and Mathematics Hardware and Architecture |
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