Energy-aware Scheduling on Multiprocessor Platforms

Li, Dawei

ISBN 10: 1461452236 ISBN 13: 9781461452232

Editorial: Springer 2012-10, 2012

Idioma: Ingl�s

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Detalles bibliogr�ficos

T�tulo

Energy-aware Scheduling on Multiprocessor Platforms

Editor

Springer 2012-10

Fecha de publicaci�n

2012

Idioma

Ingl�s

ISBN 10

1461452236

ISBN 13

9781461452232

Encuadernaci�n

Estado

New

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Sinopsis

Multiprocessor platforms play important roles in modern computing systems, and appear in various applications, ranging from energy-limited hand-held devices to large data centers. As the performance requirements increase, energy-consumption in these systems also increases signiﬁcantly. Dynamic Voltage and Frequency Scaling (DVFS), which allows processors to dynamically adjust the supply voltage and the clock frequency to operate on diﬀerent power/energy levels, is considered an eﬀective way to achieve the goal of energy-saving. This book surveys existing works that have been on energy-aware task scheduling on DVFS multiprocessor platforms.

Energy-aware scheduling problems are intrinsically optimization problems, the formulations of which greatly depend on the platform and task models under consideration. Thus, Energy-aware Scheduling on Multiprocessor Platforms covers current research on this topic and classiﬁes existing works according to two key standards, namely, homogeneity/heterogeneity of multi�processor platforms and the task types considered. Under this classiﬁcation, other sub-issues are also included, such as, slack reclamation, ﬁxed/dynamic priority sched�uling, partition-based/global scheduling, and application-speciﬁc power consumption, etc.

Rese�a del editor

Multiprocessor platforms play important roles in modern computing systems, and appear in various applications, ranging from energy-limited hand-held devices to large data centers. As the performance requirements increase, energy-consumption in these systems also increases significantly. Dynamic Voltage and Frequency Scaling (DVFS), which allows processors to dynamically adjust the supply voltage and the clock frequency to operate on different power/energy levels, is considered an effective way to achieve the goal of energy-saving. This book surveys existing works that have been on energy-aware task scheduling on DVFS multiprocessor platforms.

Energy-aware scheduling problems are intrinsically optimization problems, the formulations of which greatly depend on the platform and task models under consideration. Thus, Energy-aware Scheduling on Multiprocessor Platforms covers current research on this topic and classifies existing works according to two key standards, namely, homogeneity/heterogeneity of multi�processor platforms and the task types considered. Under this classification, other sub-issues are also included, such as, slack reclamation, fixed/dynamic priority sched�uling, partition-based/global scheduling, and application-specific power consumption, etc.

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