Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Mining System for Community Finding and Centrality of Virtual User Network on the Internet

Abstract: Community finding of virtual user network on the Internet has provoked more and more researchers? interests in the field of computer and physics field recently. Existed results focus on how to seek a reasonable and feasible algorithm to find the communities of virtual user network mostly, but scarcely relate to the centrality of those found communities. In addition, the centrality of those found communities is usually not involved. In this paper, the topology of virtual user network is analyzed firstly, and it shows that the network has a scale-free characteristic. The straightforward and effective criterion evaluating the correctness to detect the community structure has been established. Then the mining system for community finding and centrality of the network is designed and its workflow is presented. Two key modules of this system, community finding module and centrality module, are studied in detail. An implementation example is given to verify the validity of the design. Finally, the paper is summarized.

Performance Modeling, Stochastic Networks, and Statistical Multiplexing: Second Edition

Abstract: This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in computing performance measures. The monograph also covers stochastic network theory including Markovian networks. Recent results on network utility optimization and connections to stochastic insensitivity are discussed. Also presented are ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. In particular, the important concept of effective bandwidths as mappings from queueing level phenomena to loss network models is clearly presented along with a detailed discussion of accurate approximations for large networks. Table of Contents: Introduction to Traffic Models and Analysis / Queues and Performance Analysis / Loss Models for Networks / Stochastic Networks and Insensitivity / Statistical Multiplexing

Detecting global bridges in networks

Abstract: The identification of nodes occupying important positions in a network structure is crucial for the understanding of the associated real-world system. Usually, betweenness centrality is used to evaluate a node capacity to connect different graph regions. However, we argue here that this measure is not adapted for that task, as it gives equal weight to "local" centers (i.e. nodes of high degree central to a single region) and to "global" bridges, which connect different communities. This distinction is important as the roles of such nodes are different in terms of the local and global organisation of the network structure. In this paper we propose a decomposition of betweenness centrality into two terms, one highlighting the local contributions and the other the global ones. We call the latter bridgeness centrality and show that it is capable to specifically spot out global bridges. In addition, we introduce an effective algorithmic implementation of this measure and demonstrate its capability to identify global bridges in air transportation and scientific collaboration networks.

Information spreading in Online Social Networks: A case study on Twitter network

Abstract: Information propagation in online social media draw attention in different research domains due to it's influence and importance in public domain. The complexity of this research problem arises due to its huge volume and transient nature. For different user domain data processing, methodologies and derivations of information spreading are quite different in nature. In this paper, we study information propagation in online social network twitter, considering different centrality measures and simulate through random walk. Assuming that the structure of these websites is a kind of scale free network but exhibits the property of small world network, we compare information propagation to sight the most pivotal nodes in the network in aspect of information propagation.