Real-Time Systems
Scalable Parallel Computing: Technology,Architecture,Programming
Scalable Parallel Computing: Technology,Architecture,Programming
Energy efficient CMOS microprocessor design
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Power-Aware Resource Allocation for Independent Tasks in Heterogeneous Real-Time Systems
ICPADS '02 Proceedings of the 9th International Conference on Parallel and Distributed Systems
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Energy-Efficient Scheduling for Parallel Applications Running on Heterogeneous Clusters
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
Power-Aware Real-Time Scheduling upon Identical Multiprocessor Platforms
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
Computers and Electrical Engineering
Overview of the Blue Gene/L system architecture
IBM Journal of Research and Development
NP-complete scheduling problems
Journal of Computer and System Sciences
Rolling-horizon scheduling for energy constrained distributed real-time embedded systems
Journal of Systems and Software
ACM SIGOPS Operating Systems Review
Dynamic Voltage Scaling Scheduling on Power-Aware Clusters under Power Constraints
DS-RT '13 Proceedings of the 2013 IEEE/ACM 17th International Symposium on Distributed Simulation and Real Time Applications
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Nowadays, power reducing has become a critical issue in clusters for minimizing electricity cost, improving system reliability and protecting environment. Consequently, developing power-aware scheduling strategies for applications on clusters, especially on heterogeneous clusters is highly desirable. We propose in this paper an adaptive power-aware scheduling strategy called APAS for a periodic real-time tasks on DVS-enabled heterogeneous clusters. APAS takes the scheduliability, power consumption, and system load into consideration. While scheduling, APAS is capable of adaptively adjusting voltage levels according to the system load. When the system is in heavy load, APAS increases voltage levels to improve scheduliability. In contrast, when the system is lightly loaded, APAS degrades voltage levels to reduce power consumption while guaranteeing high scheduliability. Compared with Greedy, SLVL and SHVL, APAS shows obvious excellent scheduling quality to others by simulation experiments.