Voltage scheduling in the IpARM microprocessor system
ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
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
Voltage-Clock Scaling for Low Energy Consumption in Real-Time Embedded Systems
RTCSA '99 Proceedings of the Sixth International Conference on Real-Time Computing Systems and Applications
Maximizing the System Value while Satisfying Time and Energy Constraints
RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
Uncertainty-based scheduling: energy-efficient ordering for tasks with variable execution time
Proceedings of the 2003 international symposium on Low power electronics and design
Energy-efficient soft real-time CPU scheduling for mobile multimedia systems
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
PACE: A New Approach to Dynamic Voltage Scaling
IEEE Transactions on Computers
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
Policies for dynamic clock scheduling
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Energy aware kernel for hard real-time systems
Proceedings of the 2005 international conference on Compilers, architectures and synthesis for embedded systems
Dynamic voltage scaling for multitasking real-time systems with uncertain execution time
GLSVLSI '06 Proceedings of the 16th ACM Great Lakes symposium on VLSI
Procrastinating voltage scheduling with discrete frequency sets
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Energy-aware scheduling for real-time multiprocessor systems with uncertain task execution time
Proceedings of the 44th annual Design Automation Conference
A unified practical approach to stochastic DVS scheduling
EMSOFT '07 Proceedings of the 7th ACM & IEEE international conference on Embedded software
Minimizing expected energy consumption in real-time systems through dynamic voltage scaling
ACM Transactions on Computer Systems (TOCS)
Expected energy consumption minimization in DVS systems with discrete frequencies
Proceedings of the 2008 ACM symposium on Applied computing
Expected system energy consumption minimization in leakage-aware DVS systems
Proceedings of the 13th international symposium on Low power electronics and design
Operating system scheduling for efficient online self-test in robust systems
Proceedings of the 2009 International Conference on Computer-Aided Design
Minimizing expected energy consumption through optimal integration of DVS and DPM
Proceedings of the 2009 International Conference on Computer-Aided Design
Panoptic DVS: a fine-grained dynamic voltage scaling framework for energy scalable CMOS design
ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
A probabilistic and energy-efficient scheduling approach for online application in real-time systems
Proceedings of the 47th Design Automation Conference
Quasi-static voltage scaling for energy minimization with time constraints
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
On line power optimization of data flow multi-core architecture based on vdd-hopping for local DVFS
PATMOS'10 Proceedings of the 20th international conference on Integrated circuit and system design: power and timing modeling, optimization and simulation
T-Alloc: A practical energy efficient resource allocation algorithm for traditional data centers
Future Generation Computer Systems
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This paper presents an optimal procrastinating voltage scheduling (OP-DVS) for hard real-time systems using stochastic workload information. Algorithms are presented for both single-task and multi-task workloads. Offline calculations provide real-time guarantees for worst-case execution, and online scheduling reclaims slack time and schedules tasks accordingly. The OP-DVS algorithm is provably optimal in terms of energy minimization with no deadline misses. Simulation results show up to 30% energy savings for single-task workloads and 74% for multi-task workloads compared to using a constant worst-case execution voltage. The complexity of the algorithm for multi-task workloads is linear to the number of tasks involved.