On-line scheduling of hard real-time tasks on variable voltage processor

Hong, I.; Potkonjak, M.; Srivastava, M.B.

doi:10.1109/iccad.1998.743089

Cited by 12 publications

(15 citation statements)

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“…They also designed the algorithm to accept the highest possible number of online tasks that can be guaranteed to meet their deadlines. 7 Shin et al proposed a power-efficient version of fixed-priority preemptive scheduling, which is widely used in hard real-time system design. 8 Their method reduces energy consumption in the processor by exploiting systeminherent slack times, as well as slack times arising from dynamic variations of execution times for the task.…”

Section: Related Workmentioning

confidence: 99%

Software energy reduction techniques for variable-voltage processors

Okuma

Yasuura

Ishihara

2001

IEEE Des. Test. Comput.

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Section: Related Workmentioning

confidence: 99%

Software energy reduction techniques for variable-voltage processors

Okuma

Yasuura

Ishihara

2001

IEEE Des. Test. Comput.

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“…[4][5][6][7][8]) and online (e.g. [9,10]) strategy. While offline techniques optimize the voltage and speed of each task at compile time, online approaches do so at runtime to reduce the system power consumption.…”

Section: Introductionmentioning

confidence: 99%

Combining Genetic Algorithms Based Task Mapping and Optimal Voltage Selection for Energy-Efficient Distributed System Synthesis

Liu

Yang

Luo

et al. 2006

2006 International Conference on Communications, Circuits and Systems

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Energy consumption has become one of dominant design concerns in distributed embedded systems. Dynamic voltage scaling (DVS) techniques have been proved to be quite effective in reducing both dynamic and static power consumption simultaneously. Thus, integrating processing elements (PEs) supporting DVS techniques into distributed embedded systems synthesis becomes an imperative way to make an energy-efficient design budget. In this paper, we propose a synthesis framework, which integrates task mapping, scheduling and voltage selection together to minimize energy consumption of distributed systems. Genetic algorithms based task mapping are deployed to do task mapping in the outer loop, which can maximize the energy saving possibilities. A nonlinear programming based optimal voltage selection engine is then used in the inner loop. Unlike previous approaches, this combination is the first time to be implemented, and relevant experiment results show that, comparing to separate synthesis flows, up to 40% more energy savings are achieved.

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“…Heuristics for on-line scheduling of aperiodic tasks while not hurting the feasibility of offline periodic requests are proposed in [7]. Non-preemptive power-aware scheduling is investigated in [6].…”

Section: Relatedmentioning

confidence: 99%

“…However, the MCKP is known to be NPhard [18] which implies that it is very unlikely to design a fast (polynomial-time) exact method for its solution. From a practical point of view this means that exact methods, such as dynamic programming [18], Lagrange multipliers [1], mixed-integer linear programming [26] and enumeration schemes [7] , do not satisfy realistic temporal requirements for solving any reasonable size MCKP (that is, cannot generate a solution with milliseconds).…”

Section: The Optimization Problemmentioning

confidence: 99%

Power-optimized scheduling server for real-time tasks

Mejía-Álvarez

Levner²,

Mossé³

Proceedings. Eighth IEEE Real-Time and Embedded Technology and Applications Symposium

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In this paper we propose a novel scheduling framework for a dynamic real-time environment with energy constraints. This framework dynamically adjusts the CPU voltage/frequency so that no task in the system misses its deadline and the total energy savings of the system are maximized. In this paper we consider only realistic, discrete-Ievel speeds.Each task in the system consumes a certain amount of energy, which depends on a speed chosen for execution. The process of selecting speeds for execution while maximizing the energy savings of the system requires the exploration of a large number of combinations, which is too time consuming to be computed on-line. Thus, we propose an integrated heuristic methodology which executes an optimization procedure in a low computation time. This scheme allows the scheduler to handle power-aware realtime tasks with low cost while maximizing the use of the available resources and without jeopardizing the temporal constraints of the system. Simulation results show that our heuristic methodology is able to generate power-aware scheduling solutions with near-optimal performance.

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On-line scheduling of hard real-time tasks on variable voltage processor

Cited by 12 publications

References 0 publications

Software energy reduction techniques for variable-voltage processors

Software energy reduction techniques for variable-voltage processors

Combining Genetic Algorithms Based Task Mapping and Optimal Voltage Selection for Energy-Efficient Distributed System Synthesis

Power-optimized scheduling server for real-time tasks

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