
Autonomic Clustering of Distributed Agents
Elizabeth Ogston(Author)
Birkhauser Verlag AG
Will be published approx. on 2. February 2100
Book
Paperback/Softback
160 pages
978-3-7643-9966-5 (ISBN)
Description
A central principle in the design of large-scale distributed systems is that components should be organized to place those that interact frequently close together. This is essentially a basic clustering problem, but the context creates new challenges. Traditional clustering algorithms are designed to work on relatively simple units of information stored in a centralized database. This work explores the consequences of clustering autonomous entities, each with individual, possibly different, criteria defining similarity and cluster composition requirements. In this setting clustering is transformed from being mainly a catagorization task, into a problem of discovering similarity criteria and classification categories. Original research results define a general model of decentralized clustering of autonomous entities, and present simulations investigating key process, from matchmaking, to catagorization, to learning behaviors needed for adaptive cluster discovery.
More details
Series
Edition
2012
Language
English
Place of publication
Basel
Switzerland
Target group
Professional and scholarly
Research
Illustrations
biography
Dimensions
Height: 235 mm
Width: 155 mm
ISBN-13
978-3-7643-9966-5 (9783764399665)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Preface.- 1 Introduction.- 2 Model and Notation.- 3 Matchmaking.- 4 Auctions.- 5 Grouping Matchmaking Agents.- 6 Clustering 2D Spatial Data.- 7 Clustering Text.- 8 Adaptive Clusters.- 9 Summation.- Bibliography.