Hard real-time scheduling for low-energy using stochastic data and DVS processors
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Energy-Aware Partitioning for Multiprocessor Real-Time Systems
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Minimum and Maximum Utilization Bounds for Multiprocessor RM Scheduling
ECRTS '01 Proceedings of the 13th Euromicro Conference on Real-Time Systems
Power-Aware Scheduling for Periodic Real-Time Tasks
IEEE Transactions on Computers
An Approximation Algorithm for Energy-Efficient Scheduling on A Chip Multiprocessor
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Worst-case utilization bound for EDF scheduling on real-time multiprocessor systems
Euromicro-RTS'00 Proceedings of the 12th Euromicro conference on Real-time systems
Power efficient rate monotonic scheduling for multi-core systems
Journal of Parallel and Distributed Computing
| Hi-index | 0.00 |
Multicore processors promise higher throughput at lower power consumption than single core processors. Thus in the near future they will be widely used in hard real-time systems as the performance requirements are increasing. Though DVS may reduce power consumption for hard real time applications on single core processors, it introduces a new implication for multicore systems since all the cores in a chip should run at the same performance. Blind adoption of existing DVS algorithms may result in waste of energy since a core which requires low performance should run at the same high frequency with other cores. Based on the existing partitioning algorithms for the multiprocessor hard real-time scheduling, this article presents dynamic task repartitioning algorithm that balances task loads among cores to avoid the phenomena dynamically during execution. Simulation results show that in general cases our scheme makes additional energy saving more than 10% than that without our scheme even when the schedules are generated by WFD partitioning algorithm which is known as the best energy efficient partitioning algorithm