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IEEE Transactions on Network Science and Engineering

Issue 1 • Jan.-June 1 2014

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Displaying Results 1 - 7 of 7
  • IEEE TNSE Inaugural Issue Editorial

    Publication Year: 2014, Page(s): 1
    Request permission for commercial reuse | PDF file iconPDF (55 KB) | HTML iconHTML
    Freely Available from IEEE
  • IEEE Transactions on Network Science and Engineering

    Publication Year: 2014, Page(s):2 - 9
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    Freely Available from IEEE
  • Decoding Binary Node Labels from Censored Edge Measurements: Phase Transition and Efficient Recovery

    Publication Year: 2014, Page(s):10 - 22
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (362 KB) | HTML iconHTML

    We consider the problem of clustering a graph G into two communities by observing a subset of the vertex correlations. Specifically, we consider the inverse problem with observed variables Y = BGx ⊕ Z, where BG is the incidence matrix of a graph G, x is the vector of unknown vertex variables (with a uniform prior), and Z is a noise vector with Bernoulli (ε) i.i.... View full abstract»

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  • Distributed Online Convex Optimization Over Jointly Connected Digraphs

    Publication Year: 2014, Page(s):23 - 37
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (548 KB) | HTML iconHTML

    This paper considers networked online convex optimization scenarios from a regret analysis perspective. At each round, each agent in the network commits to a decision and incurs in a local cost given by functions that are revealed over time and whose unknown evolution model might be adversarially adaptive to the agent's behavior. The goal of each agent is to incur a cumulative cost over time with ... View full abstract»

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  • A Brief Survey of PageRank Algorithms

    Publication Year: 2014, Page(s):38 - 42
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (129 KB) | HTML iconHTML

    We examine several PageRank approximation algorithms. Quantitative analyses are provided to illustrate the extraordinary effectiveness of the PageRank computation. View full abstract»

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  • All-to-All Communication in Random Regular Directed Graphs

    Publication Year: 2014, Page(s):43 - 52
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (312 KB) | HTML iconHTML

    We consider networks formed by the union of M random 1-regular directed graphs. These graphs are also called permutation models in the literature. We first present a proof showing that the expansion factor of such graphs is greater than or equal to log N a.a.s when M > 4 log N; where N is the number of nodes in the network. The reason for considering such random graph models is their applicabil... View full abstract»

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  • Robust Network Routing under Cascading Failures

    Publication Year: 2014, Page(s):53 - 66
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (510 KB) | HTML iconHTML

    We propose a dynamical model for cascading failures in single-commodity network flows. In the proposed model, the network state consists of flows and activation status of the links. Network dynamics is determined by a, possibly state-dependent and adversarial, disturbance process that reduces flow capacity on the links, and routing policies at the nodes that have access to the network state, but a... 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.

Full Aims & Scope

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