Energy-aware Scheduling on Multiprocessor Platforms

  • Dawei Li
  • Jie Wu

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-vii
  2. Dawei Li, Jie Wu
    Pages 1-2
  3. Dawei Li, Jie Wu
    Pages 3-11
  4. Dawei Li, Jie Wu
    Pages 53-54
  5. Dawei Li, Jie Wu
    Pages 55-56
  6. Back Matter
    Pages 57-59

About this book


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 multi­processor platforms and the task types considered. Under this classification, other sub-issues are also included, such as, slack reclamation, fixed/dynamic priority sched­uling, partition-based/global scheduling, and application-specific power consumption, etc.


Energy/power-aware Task Scheduling Heterogeneous Platform Homogeneous Platform Multi-core Multiprocessor

Authors and affiliations

  • Dawei Li
    • 1
  • Jie Wu
    • 2
  1. 1., Department of ComputerTemple UniversityPhiladelphiaUSA
  2. 2.Temple UniversityPhiladelphiaUSA

Bibliographic information

  • DOI
  • Copyright Information The Author(s) 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-5223-2
  • Online ISBN 978-1-4614-5224-9
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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