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A Graph-Theoretic Approach to Enterprise Network Dynamics (Progress in Computer Science and Applied Logic), by Horst Bunke, Peter J. Dicki
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This monograph treats the application of numerous graph-theoretic algorithms to a comprehensive analysis of dynamic enterprise networks. Network dynamics analysis yields valuable information about network performance, efficiency, fault prediction, cost optimization, indicators and warnings. Based on many years of applied research on generic network dynamics, this work covers a number of elegant applications (including many new and experimental results) of traditional graph theory algorithms and techniques to computationally tractable network dynamics analysis to motivate network analysts, practitioners and researchers alike.
- Sales Rank: #1225872 in Books
- Brand: Brand: Birkhäuser
- Published on: 2006-12-01
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x .56" w x 6.14" l, 1.00 pounds
- Binding: Hardcover
- 226 pages
- Used Book in Good Condition
Review
From the reviews:
"This book introduces various graph theory topics, and shows how these concepts can be used to solve some of the real problems that arise in these five functional areas. … It is more suitable for research professors working with data networks, graduate students in the subject, or advanced undergrads in discrete mathematics." (G. M. White, Computing Reviews, Vol. 50 (1), January, 2009)
"This monograph focusses on the dynamic nature of networks. It provides guidance in answering questions concerning the detection and identification of faults … . Most mathematicians will appreciate the applications … and at the same time find numerous open problems in mathematics suggested by the needs of dynamic network modelling. … The monograph should prove interesting not only to network managers, but also to mathematicians in a variety of fields. … it provides a good starting point for the underlying mathematics." (Charles J. Colbourn, Zentralblatt MATH, Vol. 1157, 2009)
From the Back Cover
Networks have become nearly ubiquitous and increasingly complex, and their support of modern enterprise environments has become fundamental. Accordingly, robust network management techniques are essential to ensure optimal performance of these networks. This monograph treats the application of numerous graph-theoretic algorithms to a comprehensive analysis of dynamic enterprise networks. Network dynamics analysis yields valuable information about network performance, efficiency, fault prediction, cost optimization, indicators and warnings.
The exposition is organized into four relatively independent parts: an introduction and overview of typical enterprise networks and the graph theoretical prerequisites for all algorithms introduced later; an in-depth treatise of usage of various graph distances for event detection; a detailed exploration of properties of underlying graphs with modeling applications; and a theoretical and applied treatment of network behavior inferencing and forecasting using sequences of graphs.
Based on many years of applied research on generic network dynamics, this work covers a number of elegant applications (including many new and experimental results) of traditional graph theory algorithms and techniques to computationally tractable network dynamics analysis to motivate network analysts, practitioners and researchers alike. The material is also suitable for graduate courses addressing state-of-the-art applications of graph theory in analysis of dynamic communication networks, dynamic databasing, and knowledge management.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Interesting graph theory applications to network dynamics analysis
By Steve Uhlig
This book principally deals with the application of graph-theoretic algorithms (matching, similarity measures, graph change detection, clustering,...) to real-world networks. The focus of the book is on the graph-theoretic tools, i.e. adapting theoretical tools to get insight into the dynamics of networks.
In the first part, the authors review the state-of-the-art in network management and monitoring, and review the current work on anomaly detection. Some background on graph theory is also presented in the second chapter.
In the second and main part, the authors apply in each of the 6 chapters graph-theoretic tools and concepts on a particular problem. Emphasis is put on the computational cost of the techniques. Many interesting problems for detecting abnormal changes in graph dynamics are proposed based on edit distance and graph clustering.
In the third part, topological metrics are used to better understand the structure of enterprise networks. Tournament scoring is also proposed to rank the nodes by their importance in communications.
The fourth and last part deals with the problem of recovering missing information from graphs. Trying to recover missing information helps to reduce the risk of false alarms in abnormal change.
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