By Horst Bunke, Peter J. Dickinson, Miro Kraetzl, Walter D. Wallis
Networks became approximately ubiquitous and more and more complicated, and their help of contemporary firm environments has turn into primary. for that reason, strong community administration options are necessary to confirm optimum functionality of those networks. This monograph treats the applying of diverse graph-theoretic algorithms to a entire research of dynamic firm networks. community dynamics research yields invaluable information regarding community functionality, potency, fault prediction, expense optimization, symptoms and warnings.The exposition is geared up into 4 quite autonomous elements: an advent and review of commonplace company networks and the graph theoretical necessities for all algorithms brought later; an in-depth treatise of utilization of assorted graph distances for occasion detection; a close exploration of houses of underlying graphs with modeling functions; and a theoretical and utilized remedy of community habit inferencing and forecasting utilizing sequences of graphs.Based on a long time of utilized learn on widely used community dynamics, this paintings covers a couple of stylish functions (including many new and experimental effects) of conventional graph concept algorithms and strategies to computationally tractable community dynamics research to encourage community analysts, practitioners and researchers alike. the cloth is additionally appropriate for graduate classes addressing cutting-edge functions of graph conception in research of dynamic communique networks, dynamic databasing, and data administration.
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Additional info for A Graph-Theoretic Approach to Enterprise Network Dynamics
The information from OD trafﬁc ﬂows can be represented as a graph. Graph-based techniques can then be used to produce measures that are sensitive to network change and hence be used in network anomaly detection. Such and other techniques applied to analysis of enterprise network dynamics indeed represent the main topics of this monograph. 2 Common Monitoring Solutions for Intranets SNMP-based polling systems have proven to be cost-effective means for network monitoring due to the widespread deployment of devices that are SNMP enabled.
1 Introduction We are going to discuss the structure of several kinds of communications networks. In every case, the network consists of a number of individuals, or nodes, and certain relationships between them. The basic mathematical structure underlying this is a graph. A graph consists of undeﬁned objects called vertices together with a binary relation called adjacency: given any two vertices, either they are adjacent or they are not. Vertices will usually represent nodes or collections of nodes of the network; for example, they might be individuals in an organization, or servers in an intranet.
This requires a large range of network measures to be considered. It is critical that the measurement variables selected enable modeling of normal network behavior and be sensitive to network abnormalities of interest. 6) so that single time series analysis can be utilized. Alternatively, techniques based on analysis of multiple time series, or multivariate analysis, such as principal component analysis, may be used. 7 Network Anomaly Detection and Network Anomalies 25 Statistical techniques are likely to have the disadvantage of producing a larger number of false alarms and may not be able to identify the type of anomaly detected.
A Graph-Theoretic Approach to Enterprise Network Dynamics by Horst Bunke, Peter J. Dickinson, Miro Kraetzl, Walter D. Wallis