Adaptive Load-Balancing Algorithms Using Symmetric Broadcast Networks (Paperback)


In a distributed computing environment, it is important to ensure that the processor workloads are adequately balanced, Among numerous load-balancing algorithms, a unique approach due to Das and Prasad defines a symmetric broadcast network (SBN) that provides a robust communication pattern among the processors in a topology-independent manner. In this paper, we propose and analyze three efficient SBN-based dynamic load-balancing algorithms, and implement them on an SGI Origin2000. A thorough experimental study with Poisson distributed synthetic loads demonstrates that our algorithms are effective in balancing system load. By optimizing completion time and idle time, the proposed algorithms are shown to compare favorably with several existing approaches.

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Product Description

In a distributed computing environment, it is important to ensure that the processor workloads are adequately balanced, Among numerous load-balancing algorithms, a unique approach due to Das and Prasad defines a symmetric broadcast network (SBN) that provides a robust communication pattern among the processors in a topology-independent manner. In this paper, we propose and analyze three efficient SBN-based dynamic load-balancing algorithms, and implement them on an SGI Origin2000. A thorough experimental study with Poisson distributed synthetic loads demonstrates that our algorithms are effective in balancing system load. By optimizing completion time and idle time, the proposed algorithms are shown to compare favorably with several existing approaches.

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Product Details

General

Imprint

Bibliogov

Country of origin

United States

Release date

August 2013

Availability

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

First published

August 2013

Authors

Creators

,

Dimensions

246 x 189 x 2mm (L x W x T)

Format

Paperback - Trade

Pages

34

ISBN-13

978-1-289-28858-7

Barcode

9781289288587

Categories

LSN

1-289-28858-5



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