Power efficiency study of multi-threading applications for multi-core mobile systems
WSEAS Transactions on Computers
Proceedings of the 2010 ACM Symposium on Applied Computing
Energy-efficient scheduling of real-time periodic tasks in multicore systems
NPC'10 Proceedings of the 2010 IFIP international conference on Network and parallel computing
A dynamic power-aware partitioner with task migration for multicore embedded systems
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
TL-plane-based multi-core energy-efficient real-time scheduling algorithm for sporadic tasks
ACM Transactions on Architecture and Code Optimization (TACO) - HIPEAC Papers
A run-time task migration scheme for an adjustable issue-slots multi-core processor
ARC'12 Proceedings of the 8th international conference on Reconfigurable Computing: architectures, tools and applications
Energy- and performance-aware scheduling of tasks on parallel and distributed systems
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Energy and transition-aware runtime task scheduling for multicore processors
Journal of Parallel and Distributed Computing
A scheduling algorithm to reduce the static energy consumption of multiprocessor real-time systems
Proceedings of the 21st International conference on Real-Time Networks and Systems
A heuristic energy-aware approach for hard real-time systems on multi-core platforms
Microprocessors & Microsystems
Energy-credit scheduler: An energy-aware virtual machine scheduler for cloud systems
Future Generation Computer Systems
DFTS: A dynamic fault-tolerant scheduling for real-time tasks in multicore processors
Microprocessors & Microsystems
Analysis of virtual machine live-migration as a method for power-capping
The Journal of Supercomputing
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Multicore processors deliver a higher throughput at lower power consumption than unicore pro- cessors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modified for multicore processors, however, since normally all the cores in a chip must run at the same performance level. Thus blindly adopting existing DVS algorithms which do not consider the restriction will result in a waste of energy. This article suggests Dynamic Repartitioning algorithm based on existing partitioning approaches of multiprocessor systems. The algorithm dynamically balances the task loads of multiple cores to optimize power consumption during execution. We also suggest Dynamic Core Scaling algorithm which adjusts the number of active cores to reduce leakage power consumption under low load conditions. Simulation results show that Dynamic Repartitioning can produce energy savings of about 8% even with the best energy-efficient partitioning algorithm. The results also show that Dynamic Core Scaling can reduce energy consumption by about 26% under low load conditions.