A Fault-Tolerant Dynamic Scheduling Algorithm for Multiprocessor Real-Time Systems and Its Analysis
IEEE Transactions on Parallel and Distributed Systems
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
A Fault-Tolerant Scheduling Algorithm for Real-Time Periodic Tasks with Possible Software Faults
IEEE Transactions on Computers
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Fault-Tolerant Real-Time Scheduling under Execution Time Constraints
RTCSA '99 Proceedings of the Sixth International Conference on Real-Time Computing Systems and Applications
Adaptive fault tolerance and graceful degradation under dynamic hard real-time scheduling
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
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
IEEE Transactions on Parallel and Distributed Systems
Power-aware QoS Management in Web Servers
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Making a Case for Efficient Supercomputing
Queue - Power Management
Scheduling Processor Voltage and Frequency in Server and Cluster Systems
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 11 - Volume 12
Scheduling Security-Critical Real-Time Applications on Clusters
IEEE Transactions on Computers
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
A non-preemptive scheduling algorithm for soft real-time systems
Computers and Electrical Engineering
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)
IEEE Transactions on Parallel and Distributed Systems
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
SAQA: A Self-Adaptive QoS-Aware Scheduling Algorithm for Real-Time Tasks on Heterogeneous Clusters
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Optimizing performance and energy in computational grids using non-cooperative game theory
GREENCOMP '10 Proceedings of the International Conference on Green Computing
QoS-Aware Fault-Tolerant Scheduling for Real-Time Tasks on Heterogeneous Clusters
IEEE Transactions on Computers
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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Developing energy-efficient clusters not only can reduce power electricity cost but also can improve system reliability. Existing scheduling strategies developed for energy-efficient clusters conserve energy at the cost of performance. The performance problem becomes especially apparent when cluster computing systems are heavily loaded. To address this issue, we propose in this paper a novel scheduling strategy-adaptive energy-efficient scheduling or AEES-for aperiodic and independent real-time tasks on heterogeneous clusters with dynamic voltage scaling. The AEES scheme aims to adaptively adjust voltages according to the workload conditions of a cluster, thereby making the best trade-offs between energy conservation and schedulability. When the cluster is heavily loaded, AEES considers voltage levels of both new tasks and running tasks to meet tasks' deadlines. Under light load, AEES aggressively reduces the voltage levels to conserve energy while maintaining higher guarantee ratios. We conducted extensive experiments to compare AEES with an existing algorithm-MEG, as well as two baseline algorithms-MELV, MEHV. Experimental results show that AEES significantly improves the scheduling quality of MELV, MEHV and MEG.