# IEEE Transactions on Network Science and Engineering

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• ### Information Propagation in Clustered Multilayer Networks

Publication Year: 2016, Page(s):211 - 224
Cited by:  Papers (3)
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In today's world, individuals interact with each other in more complicated patterns than ever. Some individuals engage through online social networks (e.g., Facebook, Twitter), while some communicate only through conventional ways (e.g., face-to-face). Therefore, understanding the dynamics of information propagation among humans calls for a multi-layer network model where an online social network ... View full abstract»

• ### SIS Epidemic Spreading with Heterogeneous Infection Rates

Publication Year: 2017, Page(s):177 - 186
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In this work, we aim to understand the influence of the heterogeneity of infection rates on the Susceptible-Infected-Susceptible (SIS) epidemic spreading. Employing the classic SIS model as the benchmark, we study the influence of the independently identically distributed infection rates on the average fraction of infected nodes in the metastable state. The log-normal, gamma and a newly designed d... View full abstract»

• ### Community Detection and Classification in Hierarchical Stochastic Blockmodels

Publication Year: 2017, Page(s):13 - 26
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In disciplines as diverse as social network analysis and neuroscience, many large graphs are believed to be composed of loosely connected smaller graph primitives, whose structure is more amenable to analysis We propose a robust, scalable, integrated methodology for community detection and community comparison in graphs. In our procedure, we first embed a graph into an appropriate Euclidean space ... View full abstract»

• ### On Detection and Structural Reconstruction of Small-World Random Networks

Publication Year: 2017, Page(s):165 - 176
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In this paper, we study detection and fast reconstruction of the celebrated Watts-Strogatz (WS) small-world random graph model [29] which aims to describe real-world complex networks that exhibit both high clustering and short average length properties. The WS model with neighborhood size k and rewiring probability probability β can be viewed as a continuous interpolation between a determin... View full abstract»

• ### Diffusion of Innovation in Large Scale Graphs

Publication Year: 2017, Page(s):100 - 111
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Will a new smartphone application diffuse deeply in the population or will it sink into oblivion soon? To predict this, we argue that common models of spread of innovations based on cascade dynamics or epidemics may not be fully adequate. In this paper, we model the spread of a new technological item in a population through a novel network dynamics where diffusion is based on the word-of-mouth and... View full abstract»

• ### Fast Generation of Spatially Embedded Random Networks

Publication Year: 2017, Page(s):112 - 119
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Spatially Embedded Random Networks such as the Waxman random graph have been used in many settings for synthesizing networks. Prior to our work, there existed no software for generating these efficiently. Existing techniques are $O(n^2)$ where ... View full abstract»

• ### Hyperbolic Embedding for Efficient Computation of Path Centralities and Adaptive Routing in Large-Scale Complex Commodity Networks

Publication Year: 2017, Page(s):140 - 153
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Computing the most central nodes in large-scale commodity networks is rather important for improving routing and associated applications. In this paper, we introduce a novel framework for the analysis and efficient computation of routing path-based centrality measures, focusing on betweenness and traffic load centrality. The proposed framework enables efficient approximation and in special cases a... View full abstract»

• ### Inference of Hidden Social Power Through Opinion Formation in Complex Networks

Publication Year: 2017, Page(s):154 - 164
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Social networks analysis and mining gets ever-increasing importance in various disciplines. In this context finding the most influential nodes with the highest social power is important in many applications including spreading of innovation, opinion formation, immunization, information propagation and recommendation. In this manuscript, we propose a mathematical framework in order to effectively e... View full abstract»

• ### The Power of Quasi-Shortest Paths: $\rho$ -Geodesic Betweenness Centrality

Publication Year: 2017, Page(s):187 - 200
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Betweenness centrality metrics usually underestimate the importance of nodes that are close to shortest paths but do not exactly fall on them. In this paper, we reevaluate the importance of such nodes and propose the p-geodesic betweenness centrality, a novel metric that assigns weights to paths (and, consequently, to nodes on these paths) according to how close they are to shortest paths. The pat... View full abstract»

• ### Belief Dynamics in Social Networks: A Fluid-Based Analysis

Publication Year: 2017, Page(s): 1
| | PDF (436 KB) |  Media

The advent and proliferation of social media have led to the development of mathematical models describing the evolution of beliefs/opinions in an ecosystem composed of socially interacting users. The goal is to gain insights into collective dominant social beliefs and into the impact of different components of the system, such as users' interactions, while being able to predict users... View full abstract»

• ### A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation And Integration Concept

Publication Year: 2017, Page(s): 1
| | PDF (3456 KB)

A Self-Organising Cloud Radio Access Network (C-RAN) is proposed, which dynamically adapt to varying capacity demands. The Base Band Units and Remote Radio Heads are scaled semi-statically based on the concept of cell differentiation and integration (CDI) while a dynamic load balancing is formulated as an integer-based optimisation problem with constraints. A Discrete Particle Swarm Optimisation (... View full abstract»

• ### Spreading Processes in Multilayer Networks

Publication Year: 2015, Page(s):65 - 83
Cited by:  Papers (20)
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Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while inf... View full abstract»

• ### Network Maximal Correlation

Publication Year: 2017, Page(s): 1
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We introduce Network Maximal Correlation (NMC) as a multivariate measure of nonlinear association among random variables. NMC is defined via an optimization that infers transformations of variables by maximizing aggregate inner products between transformed variables. For finite discrete and jointly Gaussian random variables, we characterize a solution of the NMC optimization using basis expansion ... View full abstract»

Publication Year: 2017, Page(s):129 - 139
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Large-scale cascading failures can be triggered by very few initial failures, leading to severe damages in complex networks. This paper studies load-dependent cascading failures in random networks consisting of a large but finite number of components. Under a random single-node attack, a framework is developed to quantify the damage at each stage of a cascade. Estimations and analyses for the frac... View full abstract»

• ### Finite-time Passivity of Coupled Neural Networks with Multiple Weights

Publication Year: 2017, Page(s): 1
| | PDF (4550 KB)

This paper respectively studies finite-time passivity of multi-weighted coupled neural networks (MWCNNs) with and without coupling delays. Firstly, based on those existing passivity definitions, several new concepts about finite-time passivity are presented. By exploiting these definitions for finite-time passivity and designing appropriate controllers, we investigate the passivity of MWCNNs with ... View full abstract»

• ### Competitive Propagation: Models, Asymptotic Behavior and Quality-Seeding Games

Publication Year: 2017, Page(s):83 - 99
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In this paper we propose a class of propagation models for multiple competing products over a social network. We consider two propagation mechanisms: social conversion and self conversion, corresponding, respectively, to endogenous and exogenous factors. A novel concept, the product-conversion graph, is proposed to characterize the interplay among competing products. According to the chronological... View full abstract»

• ### Comparing the Effects of Failures in Power Grids under the AC and DC Power Flow Models

Publication Year: 2017, Page(s): 1
| | PDF (1542 KB) |  Media

In this paper, we compare the effects of failures in power grids under the nonlinear AC and linearized DC power flow models. First, we numerically demonstrate that when there are no failures and the assumptions underlying the DC model are valid, the DC model approximates the AC model well in four considered test networks. Then, to evaluate the validity of the DC approximation upon failures, we num... View full abstract»

• ### Weighted Bearing-Compass Dynamics: Edge and Leader Selection

Publication Year: 2017, Page(s): 1
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This paper considers the design and effective interfaces of a distributed robotic formation running planar weighted bearing-compass dynamics. We present results which support methodologies to construct formation topologies using submodular optimization techniques. Further, a convex optimization framework is developed for the selection of edge weights which increase performance. We explore a method... View full abstract»

• ### Information Cascades in Feed-Based Networks of Users with Limited Attention

Publication Year: 2017, Page(s):120 - 128
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We build a model of information cascades on feed-based networks, taking into account the finite attention span of users, message generation rates and message forwarding rates. Through simulation of this model, we study the effect of the extent of user attention on the probability that the cascade becomes viral. In analogy with a branching process, we estimate the branching factor associated with t... View full abstract»

• ### Detecting Cascades from Weak Signatures

Publication Year: 2017, Page(s): 1
| | PDF (2697 KB)

Inspired by cyber-security applications, we consider the problem of detecting an infection process in a network when the indication that any particular node is infected is extremely noisy. Instead of waiting for a single node to provide sufficient evidence that it is indeed infected, we take advantage of the graph structure to detect cascades of weak indications of failures. We view the detection ... View full abstract»

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

Publication Year: 2016, Page(s):147 - 158
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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»

• ### Modelling Spreading Process Induced by Agent Mobility in Complex Networks

Publication Year: 2017, Page(s): 1
| | PDF (35642 KB)

Most conventional epidemic models assume contact-based contagion process. We depart from this assumption and study epidemic spreading process in networks caused by agents acting as carrier of infection. These agents traverse from origins to destinations following specific paths in a network and in the process, infecting the sites they travel across. We focus our work on the Susceptible-Infected-Re... View full abstract»

• ### Synchronization of Diffusively-Connected Nonlinear Systems: Results Based on Contractions with Respect to General Norms

Publication Year: 2014, Page(s):91 - 106
Cited by:  Papers (4)
| | PDF (509 KB) | HTML

Contraction theory provides an elegant way to analyze the behavior of certain nonlinear dynamical systems. In this paper, we discuss the application of contraction to synchronization of diffusively interconnected components described by nonlinear differential equations. We provide estimates of convergence of the difference in states between components, in the cases of line, complete, and star grap... View full abstract»

• ### Recovering asymmetric communities in the stochastic block model

Publication Year: 2017, Page(s): 1
| | PDF (1823 KB) |  Media

We consider the sparse stochastic block model in the case where the degrees are uninformative. The case where the two communities have approximately the same size has been extensively studied and we concentrate here on the community detection problem in the case of unbalanced communities. In this setting, spectral algorithms based on the non-backtracking matrix are known to solve the community det... View full abstract»

• ### Isomorphisms in Multilayer Networks

Publication Year: 2017, Page(s): 1
| | PDF (389 KB)

We extend the concept of graph isomorphisms to multilayer networks with any number of “aspects” (i.e., types of layering). In developing this generalization, we identify multiple types of isomorphisms. For example, in multilayer networks with a single aspect, permuting vertex labels, layer labels, and both vertex labels and layer labels each yield different isomorphism relations betw... View full abstract»

• ### Understanding Sequential User Behavior in Social Computing: To Answer or to Vote?

Publication Year: 2015, Page(s):112 - 126
Cited by:  Papers (2)
| | PDF (713 KB) | HTML

Understanding how users participate is of key importance to social computing systems since their value is created from user contributions. In many social computing systems, users decide sequentially whether to participate or not and, if participate, whether to create a piece of content directly, i.e., answering, or to rate existing content, i.e., voting. Moreover, there exists an answering-voting ... View full abstract»

• ### Information flow in a model of policy diffusion: an analytical study

Publication Year: 2017, Page(s): 1
| | PDF (474 KB)

Networks are pervasive across science and engineering, but seldom do we precisely know their topology. The information-theoretic notion of transfer entropy has been recently proposed as a potent means to unveil connectivity patterns underlying collective dynamics of complex systems. By pairwise comparing time series of units in the network, transfer entropy promises to determine whether the units ... View full abstract»

• ### Information Diffusion in Social Networks in Two Phases

Publication Year: 2016, Page(s):197 - 210
| | PDF (710 KB)

The problem of maximizing information diffusion, given a certain budget expressed in terms of the number of seed nodes, is an important topic in social networks research. Existing literature focuses on single phase diffusion where all seed nodes are selected at the beginning of diffusion and all the selected nodes are activated simultaneously. This paper undertakes a detailed investigation of the ... View full abstract»

• ### Algebraic Connectivity Under Site Percolation in Finite Weighted Graphs

Publication Year: 2017, Page(s): 1
| | PDF (2277 KB)

We study the behavior of algebraic connectivity in a weighted graph that is subject to site percolation, random deletion of the vertices. Using a refined concentration inequality for random matrices we show in our main theorem that the (augmented) Laplacian of the percolated graph concentrates around its expectation. This concentration bound then provides a lower bound on the algebraic connectivit... View full abstract»

• ### The Strategic Formation of Multi-Layer Networks

Publication Year: 2015, Page(s):164 - 178
Cited by:  Papers (2)
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We study the strategic formation of multi-layer networks, where each layer represents a different type of relationship between the nodes in the network and is designed to maximize some utility that depends on the topology of that layer and those of the other layers. We start by generalizing distance-based network formation to the two-layer setting, where edges are constructed in one layer (with fi... View full abstract»

• ### On the Interplay Between Individuals’ Evolving Interaction Patterns and Traits in Dynamic Multiplex Social Networks

Publication Year: 2016, Page(s):32 - 43
Cited by:  Papers (3)
| | PDF (953 KB) | HTML Media

The interplay between individuals' social interactions and traits has been studied extensively but traditionally from static or homogeneous social network perspectives. The recent availability of dynamic and heterogeneous (multiplex) network data has introduced a variety of new challenges. Critically, novel computational models are needed that can cope with data dynamics and heterogeneity. In this... View full abstract»

• ### Cascading Edge Failures: A Dynamic Network Process

Publication Year: 2017, Page(s): 1
| | PDF (741 KB)

This paper studies a network process that can potentially be used to model cascading failures in networks. The Dynamic Bond Percolation (DBP) process models, through stochastic local rules, the failure or recovery of an edge (i, j) in a network. The probability that a working link fails or a failed link recovers may be independent of the state of other links or may be dependent locally on the stat... View full abstract»

• ### A bi-virus competing spreading model with generic infection rates

Publication Year: 2017, Page(s): 1
| | PDF (2994 KB) |  Media

Due to widespread applications, the multi-virus competing spreading dynamics has recently aroused considerable interests. To our knowledge, all previous competing spreading models assume infection rates that are each linear in the virus occupancy probabilities of the individuals in a population. As linear infection rates are overestimation of real infection rates, in some situations these models c... View full abstract»

• ### Pattern Formation over Multigraphs

Publication Year: 2017, Page(s): 1
| | PDF (1145 KB) |  Media

Two of the most common pattern formation mechanisms are Turing-patterning in reaction-diffusion systems and lateral inhibition of neighboring cells. In this paper, we introduce a broad dynamical model of interconnected modules to study the emergence of patterns, with the above mentioned two mechanisms as special cases. Our results do not restrict the number of modules or their complexity, allow mu... View full abstract»

• ### Analyses of the Clustering Coefficient and the Pearson Degree Correlation Coefficient of Chung's Duplication Model

Publication Year: 2016, Page(s):117 - 131
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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»

• ### A Brief Survey of PageRank Algorithms

Publication Year: 2014, Page(s):38 - 42
Cited by:  Papers (1)
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We examine several PageRank approximation algorithms. Quantitative analyses are provided to illustrate the extraordinary effectiveness of the PageRank computation. View full abstract»

• ### Analyzing Vulnerability of Power Systems with Continuous Optimization Formulations

Publication Year: 2016, Page(s):132 - 146
| | PDF (1088 KB) | HTML

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»

• ### Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs

Publication Year: 2015, Page(s):139 - 151
Cited by:  Papers (1)
| | PDF (942 KB) | HTML

Multi-agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small ... View full abstract»

• ### Rigid Network Design Via Submodular Set Function Optimization

Publication Year: 2015, Page(s):84 - 96
Cited by:  Papers (3)
| | PDF (655 KB) | HTML

We consider the problem of constructing networks that exhibit desirable algebraic rigidity properties, which can provide significant performance improvements for associated formation shape control and localization tasks. We show that the network design problem can be formulated as a submodular set function optimization problem and propose greedy algorithms that achieve global optimality or an esta... View full abstract»

• ### Data-Driven Network Resource Allocation for Controlling Spreading Processes

Publication Year: 2015, Page(s):127 - 138
Cited by:  Papers (1)
| | PDF (453 KB) | HTML

We propose a mathematical framework, based on conic geometric programming, to control a susceptible-infected-susceptible viral spreading process taking place in a directed contact network with unknown contact rates. We assume that we have access to time series data describing the evolution of the spreading process observed by a collection of sensor nodes over a finite time interval. We propose a d... View full abstract»

• ### Analysis of Partial Diffusion LMS for Adaptive Estimation Over Networks with Noisy Links

Publication Year: 2017, Page(s): 1
| | PDF (569 KB) |  Media

In partial diffusion-based least mean square (PDLMS) scheme, each node shares a part of its intermediate estimate vector with its neighbors at each iteration. In this paper, besides studying the general PDLMS scheme, we figure out how the noisy links deteriorate the network performance during the exchange of weight estimates. We investigate the steady state mean square deviation (MSD) and derive a... View full abstract»

• ### Clustering Network Layers with the Strata Multilayer Stochastic Block Model

Publication Year: 2016, Page(s):95 - 105
Cited by:  Papers (1)
| | PDF (1900 KB) | HTML

Multilayer networks are a useful data structure for simultaneously capturing multiple types of relationships between a set of nodes. In such networks, each relational definition gives rise to a layer. While each layer provides its own set of information, community structure across layers can be collectively utilized to discover and quantify underlying relational patterns between nodes. To concisel... View full abstract»

• ### Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks

Publication Year: 2014, Page(s):76 - 90
Cited by:  Papers (21)
| | PDF (1164 KB) | HTML Media

Most methods proposed to uncover communities in complex networks rely on combinatorial graph properties. Usually an edge-counting quality function, such as modularity, is optimized over all partitions of the graph compared against a null random graph model. Here we introduce a systematic dynamical framework to design and analyze a wide variety of quality functions for community detection. The qual... View full abstract»

• ### Detecting Multiple Information Sources in Networks under the SIR Model

Publication Year: 2016, Page(s):17 - 31
| | PDF (981 KB) | HTML

In this paper, we study the problem of detecting multiple information sources in networks under the Susceptible-Infected-Recovered (SIR) model. First, assuming the number of information sources is known, we develop a sample-path-based algorithm, named clustering and localization, for trees. For $g$ View full abstract»

• ### Minimizing Social Cost of Vaccinating Network SIS Epidemics

Publication Year: 2017, Page(s): 1
| | PDF (2088 KB)

Reducing the economic costs (losses) as much as possible is one of the main goals of controlling virus spreading and worm propagation on complex networks. Taking into account the interactions and conflicts of interests among egoistic individuals (nodes) in a network, we introduce the zero-determinant (ZD) strategy into our proposed non-cooperative networking vaccination game with the economic ince... View full abstract»

• ### Stochastic Subgradient Algorithms for Strongly Convex Optimization over Distributed Networks

Publication Year: 2017, Page(s): 1
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We study diffusion and consensus based optimization of a sum of unknown convex objective functions over distributed networks. The only access to these functions is through stochastic gradient oracles, each of which is only available at a different node; and a limited number of gradient oracle calls is allowed at each node. In this framework, we introduce a convex optimization algorithm based on st... View full abstract»

• ### A Mathematical Theory for Multistage Battery Switching Networks

Publication Year: 2017, Page(s): 1
| | PDF (4677 KB)

In this paper, we propose a mathematical theory for multistage battery switching networks. The theory aims to address several design issues in managing a large-scale battery system, including flexibility, reliability, efficiency, complexity (scalability) and sustainability. Our multistage battery switching network is constructed by a concatenation of various rectangular “shapes” of b... View full abstract»

Publication Year: 2016, Page(s):183 - 196
| | PDF (1339 KB)

The problem of cascading failures in cyber-physical systems is drawing much attention in lieu of different network models for a diverse range of applications. While many analytic results have been reported for the case of large networks, very few of them are readily applicable to finite-size networks. This paper studies cascading failures in load-dependent finite-size geometric networks where the ... View full abstract»

• ### The Smallest Eigenvalue of the Generalized Laplacian Matrix, with Application to Network-Decentralized Estimation for Homogeneous Systems

Publication Year: 2016, Page(s):312 - 324
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The problem of synthesizing network-decentralized observers arises when several agents, corresponding to the nodes of a network, exchange information about local measurements to asymptotically estimate their own state. The network topology is unknown to the nodes, which can rely on information about their neighboring nodes only. For homogeneous systems, composed of identical agents, we show that a... View full abstract»

• ### Networking the Boids is More Robust Against Adversarial Learning

Publication Year: 2017, Page(s): 1
| | PDF (6225 KB)

Swarm behavior using Boids-like models has been studied primarily using close-proximity spatial sensory information (e.g. vision range). In this study, we propose a novel approach in which the classic definition of boids\textquoteright neighborhood that relies on sensory perception and Euclidian space locality is replaced with graph-theoretic network-based proximity mimicking communication and soc... View full abstract»

## 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