RIVER PUBLISHERS IS AN INTERNATIONAL PUBLISHER THAT PUBLISHES RESEARCH MONOGRAPHS, PROFESSIONAL BOOKS, HANDBOOKS, EDITED VOLUMES AND JOURNALS WITH FOCUS ON KEY RESEARCH AREAS WITHIN THE FIELDS OF SCIENCE, TECHNOLOGY AND MEDICINE (STM).

River Publishers Series in Information Science and Technology Series

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

Hardback
October 2016
9788793519084
More details
  • Publisher
    River Publishers
  • Published
    25th October 2016
  • ISBN 9788793519084
  • Language English
  • Pages 160 pp.
  • Size 6.125" x 9.25"
$81.50
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October 2016
9788793519077
More details
  • Publisher
    River Publishers
  • Published
    31st October 2016
  • ISBN 9788793519077
  • Language English
  • Pages 160 pp.
  • Size 6.125" x 9.25"
$85.00

The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale many-core systems are notoriously hard to optimize. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude).

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for many-core systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonize the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements.

Technical topics presented in the book include:
• Load and Resource Models
• Admission Control
• Feedback-based Allocation and Optimization
• Search-based Allocation Heuristics
• Distributed Allocation based on Swarm Intelligence
• Value-Based Allocation

Each of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip many-core processors, grids and private cloud environments.

Leandro Soares Indrusiak

Leandro Soares Indrusiak

Piotr Dziurzanski

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Amit Kumar Singh

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