IEEE Transactions on Network Science and Engineering

Issue 3 • July-Sept. 1 2016

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Displaying Results 1 - 5 of 5
  • Analyses of the Clustering Coefficient and the Pearson Degree Correlation Coefficient of Chung's Duplication Model

    Publication Year: 2016, Page(s):117 - 131
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (698 KB) | HTML iconHTML

    Recent advances in gene expression profiling and proteomics techniques have spawn considerable interest in duplication models for modelling the evolution and growth of biological networks. In this paper, we consider the duplication model studied by Chung et al. It seems (to the best of our knowledge) that both the clustering coefficient and the Pearson degree correlation coefficient of this model ... View full abstract»

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  • Analyzing Vulnerability of Power Systems with Continuous Optimization Formulations

    Publication Year: 2016, Page(s):132 - 146
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1088 KB) | HTML iconHTML

    Potential vulnerabilities in a power grid can be exposed by identifying those transmission lines on which attacks (in the form of interference with their transmission capabilities) causes maximum disruption to the grid. In this study, we model the grid by (nonlinear) AC power flow equations, and assume that attacks take the form of increased impedance along transmission lines. We quantify disrupti... View full abstract»

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  • Design of Self-Organizing Networks: Creating Specified Degree Distributions

    Publication Year: 2016, Page(s):147 - 158
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (483 KB) | HTML iconHTML Multimedia Media

    A key problem in the study and design of complex systems is the apparent disconnection between the microscopic and the macroscopic. It is not straightforward to identify the local interactions that give rise to an observed global phenomenon, nor is it simple to design a system that will exhibit some desired global property using only local knowledge. Here we propose a methodology that allows for t... View full abstract»

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  • Effective Network Quarantine with Minimal Restrictions on Communication Activities

    Publication Year: 2016, Page(s):159 - 170
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1145 KB) | HTML iconHTML Multimedia Media

    This paper studies a network structure design problem constrained by the epidemic outbreaks. In our model, geographic locations (nodes) and their connections (edges) are modeled as a ring graph. The movement of a person is represented as a flow from one location to another. A person can be infected at a location (node), depending on the number of infected flows (persons) going through that locatio... View full abstract»

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  • Efficient Multistate Route Computation

    Publication Year: 2016, Page(s):171 - 182
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (698 KB) | HTML iconHTML

    A multi-state graph is defined as a graph where each edge is associated with a stochastic, rather than fixed, value. For cases where the stochastic value is discrete and represents a distance or time, an algorithm is presented which efficiently finds the single-source shortest paths and distances for all combinations of edge values. Infinite and negative weight values are allowed as long as there ... View full abstract»

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Aims & Scope

The IEEE Transactions on Network Science and Engineering is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level.

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Meet Our Editors

Editor-in-Chief
Dapeng Oliver Wu

University of Florida

Dept. of Electrical  &  Computer Engineering

P. O. Box 116130

Gainesville, FL 32611

Email: dpwu@ufl.edu