# IEEE Transactions on Network Science and Engineering

Includes the top 50 most frequently accessed documents for this publication according to the usage statistics for the month of

• ### Deep Learning Meets Wireless Network Optimization: Identify Critical Links

Publication Year: 2018, Page(s): 1
| | PDF (1563 KB)

With the superior capability of discovering intricate structure of large data sets, deep learning has been widely applied in various areas including wireless networking. While existing deep learning applications mainly focus on data analysis, the role it can play on fundamental research issues in wireless networks is yet to be explored. With the proliferation of wireless networking infrastructure ... View full abstract»

• ### Caching for Mobile Social Networks with Deep Learning: Twitter Analysis for 2016 U.S. Election

Publication Year: 2018, Page(s): 1
| | PDF (2908 KB)

As the rise of the portable devices, people usually access the social media such as Twitter and Facebook through wireless networks. Therefore, data transmission rates significant important to the end users. In this work, we discuss the problem of context-aware data caching in the heterogeneous small cell networks to reduce the service delay and how the device-to-device (D2D) and device-to-infrastr... View full abstract»

• ### A Bi-Virus Competing Spreading Model with Generic Infection Rates

Publication Year: 2018, Page(s):2 - 13
| | PDF (1246 KB) | HTML 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»

• ### Renewable Energy-Aware Big Data Analytics in Geo-distributed Data Centers with Reinforcement Learning

Publication Year: 2018, Page(s): 1
| | PDF (830 KB)

In the age of big data, companies tend to deploy their services in data centers rather than their own servers. The demands of big data analytics grow significantly, which leads to an extremely high electricity consumption at data centers. In this paper, we investigate the cost minimization problem of big data analytics on geo-distributed data centers connected to renewable energy sources with unpr... View full abstract»

• ### Scheduling Resource-Bounded Monitoring Devices for Event Detection and Isolation in Networks

Publication Year: 2018, Page(s):65 - 78
| | PDF (1048 KB) | HTML

In networked systems, monitoring devices such as sensors are typically deployed to monitor various target locations. Targets are the points in the physical space at which events of some interest, such as random faults or attacks, can occur. Most often, monitoring devices have limited energy supplies, and they can operate for a limited duration. As a result, energy-efficient monitoring of target lo... View full abstract»

• ### Pattern Formation over Multigraphs

Publication Year: 2018, Page(s):55 - 64
| | PDF (869 KB) | HTML 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»

• ### QTCP: Adaptive Congestion Control with Reinforcement Learning

Publication Year: 2018, Page(s): 1
| | PDF (4015 KB)

Next generation network access technologies and Internet applications have increased the challenge of providing satisfactory quality of experience for users with traditional congestion control protocols. Efforts on optimizing the performance of TCP by modifying the core congestion control method depending on specific network architectures or apps do not generalize well under a wide range of networ... View full abstract»

• ### Channel Selective Activity Recognition with WiFi: A Deep Learning Approach Exploring Wideband Information

Publication Year: 2018, Page(s): 1
| | PDF (1874 KB)

WiFi-based human activity recognition explores the correlations between body movement and the reflected WiFi signals to classify different activities. State-of-the-art solutions mostly work on a single WiFi channel and hence are quite sensitive to the quality of a particular channel. Co-channel interference in an indoor environment can seriously undermine the recognition accuracy. In this paper, w... View full abstract»

• ### SIS Epidemic Spreading with Heterogeneous Infection Rates

Publication Year: 2017, Page(s):177 - 186
| | PDF (828 KB) | HTML

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»

• ### Hierarchical Clustering of Bipartite Networks Based on Multiobjective Optimization

Publication Year: 2018, Page(s): 1
| | PDF (3845 KB)

Complex network modeling is an elegant yet powerful tool to delineate complex systems. Hierarchical clustering of complex networks can readily facilitate our comprehension of the higher order organizations of complex systems. Among all the complex network models, bipartite network is an essential part. In this paper we present a multiobjective optimization based hierarchical clustering algorithm f... View full abstract»

• ### Information Flow in a Model of Policy Diffusion: An Analytical Study

Publication Year: 2018, Page(s):42 - 54
| | PDF (948 KB) | HTML

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»

• ### REACT to Cyber Attacks on Power Grids

Publication Year: 2018, Page(s): 1
| | PDF (3984 KB)

Motivated by the recent cyber attack on the Ukrainian power grid, we study cyber attacks on power grids that affect both the physical infrastructure and the data at the control center--which therefore are cyber-physical in nature. In particular, we assume that an adversary attacks an area by: (i) remotely disconnecting some lines within the attacked area, and (ii) modifying the information receive... View full abstract»

• ### Spreading Processes in Multilayer Networks

Publication Year: 2015, Page(s):65 - 83
Cited by:  Papers (29)
| | PDF (686 KB) | HTML

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»

• ### A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems

Publication Year: 2018, Page(s): 1
| | PDF (1238 KB)

To provide fine-grained access to different dimensions of the physical world, data uploading in smart cyber-physical systems suffers novel challenges on both energy conservation and privacy preservation. It is always critical for participants to consume as little energy as possible for data uploading. However, simply pursuing energy efficiency may lead to extreme disclosure of private information,... View full abstract»

• ### Mobile Social Services with Network Externality: From Separate Pricing to Bundled Pricing

Publication Year: 2018, Page(s): 1
| | PDF (4916 KB)

Today, many wireless device providers choose to sell devices bundled with complementary mobile social services, which exhibit strong positive network externality. Taking a reverse engineering approach, this paper aims to quantify the benefits of selling devices and complementary services under the following three strategies: separate pricing, bundled pricing, and hybrid pricing (both the separate ... View full abstract»

• ### Multiplex Conductance and Gossip Based Information Spreading in Multiplex Networks

Publication Year: 2018, Page(s): 1
| | PDF (1606 KB) |  Media

In this network era, not only people are connected, different networks are also coupled through various interconnections. This kind of network of networks, or multilayer networks, has attracted research interest recently, and many beneficial features have been discovered. However, quantitative study of information spreading in such networks is essentially lacking. Despite some existing results in ... View full abstract»

• ### A Fair Mechanism for Private Data Publication in Online Social Networks

Publication Year: 2018, Page(s): 1
| | PDF (8314 KB)

Due to the tremendous growth of online social networks in both participants and collected contents, social data publication has provided an opportunity for numerous services. However, neglectfully publishing all the contents leads to severe disclosure of sensitive information due to diverse user behaviors. Therefore, there should be a thoroughly designed framework for data publication in online so... View full abstract»

• ### A Micro-Foundation of Social Capital in Evolving Social Networks

Publication Year: 2018, Page(s):14 - 31
| | PDF (3055 KB) | HTML Media

A social network confers benefits and advantages on individuals (and on groups); the literature refers to these benefits and advantages as social capital. An individual's social capital depends on its position in the network and on the shape of the network-but positions in the network and the shape of the network are determined endogenously and change as the network forms and evolves. This paper p... View full abstract»

• ### How Complex Contagions Spread Quickly in Preferential Attachment Models and Other Time-Evolving Networks

Publication Year: 2017, Page(s):201 - 214
| | PDF (350 KB) | HTML

The $k$ -complex contagion model is a social contagion model which describes the diffusion of behaviors in networks where the successful adoption of a behavior requires influence from multiple contacts. It has been argued t... View full abstract»

• ### Scalable Privacy-Preserving Participant Selection for Mobile Crowdsensing Systems: Participant Grouping and Secure Group Bidding

Publication Year: 2018, Page(s): 1
| | PDF (1739 KB)

Mobile crowdsensing (MCS) has been emerging as a new sensing paradigm where vast numbers of mobile devices are used for sensing and collecting data in various applications. Auction based participant selection has been widely used for current MCS systems to achieve user incentive and task assignment optimization. However, participant selection problems solved with auction-based approaches usually i... View full abstract»

• ### An Efficient Randomized Algorithm for Rumor Blocking in Online Social Networks

Publication Year: 2017, Page(s): 1
| | PDF (940 KB) |  Media

Social networks allow rapid spread of ideas and innovations while negative information can also propagate widely. When a user receives two opposing opinions, they tend to believe the one arrives first. Therefore, once misinformation or rumor is detected, one containment method is to introduce a positive cascade competing against the rumor. Given a budget $k$, the rumo... 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 (4)
| | 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»

• ### Online Resource Inference in Network Utility Maximization Problems

Publication Year: 2018, Page(s): 1
| | PDF (1380 KB) |  Media

The amount of transmitted data in computer networks is expected to grow considerably in the future, putting more and more pressure on the network infrastructures. In order to guarantee a good service, it then becomes fundamental to use the network resources efficiently. Network Utility Maximization (NUM) provides a framework to optimize the rate allocation when network resources are limited. Unfor... View full abstract»

• ### Information Propagation in Clustered Multilayer Networks

Publication Year: 2016, Page(s):211 - 224
Cited by:  Papers (4)
| | PDF (677 KB) | HTML

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»

• ### Scheduling Jobs across Geo-Distributed Datacenters with Max-Min Fairness

Publication Year: 2018, Page(s): 1
| | PDF (4599 KB)

It has become routine for large volumes of data to be generated, stored, and processed across geographically distributed datacenters. To run a single data analytic job on such geo-distributed data, recent research proposed to distribute its tasks across datacenters, considering both data locality and network bandwidth across datacenters. Yet, it remains an open problem in the more general case, wh... View full abstract»

• ### A Brief Survey of PageRank Algorithms

Publication Year: 2014, Page(s):38 - 42
Cited by:  Papers (3)
| | PDF (129 KB) | HTML

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

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

Publication Year: 2017, Page(s):248 - 260
| | PDF (1373 KB) | HTML

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»

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

Publication Year: 2016, Page(s):17 - 31
Cited by:  Papers (2)
| | 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»

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

Publication Year: 2017, Page(s):13 - 26
| | PDF (611 KB) | HTML Media

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»

• ### Hierarchical and Hybrid: Mobility-compatible Database-assisted Framework For Dynamic Spectrum Access

Publication Year: 2018, Page(s): 1
| | PDF (619 KB)

The protection of primary user activities plays a vital part in dynamic spectrum access. There exist many works surrounding the subject of spectrum sensing, which requires high sensing accuracy, and thus poses extra time cost. Nevertheless, the database-based access scheme is receiving an increasing amount of devotion, e.g., IEEE 802.11af for TV white space. In comparison to spectrum sensing, node... View full abstract»

• ### Mitigating Bottlenecks in Wide Area Data Analytics via Machine Learning

Publication Year: 2018, Page(s): 1
| | PDF (1321 KB)

Over the past decade, we have witnessed exponential growth in the density (petabyte-level) and breadth (across geo-distributed datacenters) of data distribution. It becomes increasingly challenging but imperative to minimize the response times of data analytic queries over multiple geo-distributed datacenters. However, existing scheduling-based solutions have largely been motivated by pre-establis... View full abstract»

• ### Hybrid Mixed-Membership Blockmodel for Inference on Realistic Network Interactions

Publication Year: 2018, Page(s): 1
| | PDF (9982 KB)

This work proposes novel hybrid mixed-membership blockmodels (HMMB) that integrate three canonical network models to capture the characteristics of real-world interactions: community structure with mixed-membership, power-law-distributed node degrees, and sparsity. This hybrid model provides the capacity needed for realism, enabling control and inference on individual attributes of interest such a... View full abstract»

• ### Structure-based Sybil Detection in Social Networks via Local Rule-based Propagation

Publication Year: 2018, Page(s): 1
| | PDF (828 KB)

Social networks are known to be vulnerable to Sybil attack, in which an attacker maintains massive Sybils to perform various malicious activities. Therefore, Sybil detection in social networks is a fundamental security research problem. Structure-based methods have been shown to be promising at detecting Sybils. Existing structure-based methods can be classified into Random Walk (RW)-based methods... View full abstract»

• ### Passivity Analysis and Pinning Control of Multi-Weighted Complex Dynamical Networks

Publication Year: 2017, Page(s): 1
| | PDF (3612 KB)

This paper studies a multi-weighted network model with different dimensions of output and input vectors. Firstly, we analyze passivity of proposed network model by employing some inequality techniques and Lyapunov functional method, and give a synchronization condition for output-strictly passive complex dynamical network with multi-weights (CDNMWs). Furthermore, by using pinning adaptive strategi... View full abstract»

• ### Network Maximal Correlation

Publication Year: 2017, Page(s):229 - 247
| | PDF (1310 KB) | HTML

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»

• ### Diffusion of Innovation in Large Scale Graphs

Publication Year: 2017, Page(s):100 - 111
| | PDF (439 KB) | HTML

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»

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

Publication Year: 2016, Page(s):197 - 210
Cited by:  Papers (2)
| | PDF (710 KB) | HTML

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»

• ### 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»

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

Publication Year: 2015, Page(s):164 - 178
Cited by:  Papers (3)
| | PDF (425 KB) | HTML

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»

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

Publication Year: 2014, Page(s):76 - 90
Cited by:  Papers (32)
| | 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»

• ### 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»

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

Publication Year: 2015, Page(s):127 - 138
Cited by:  Papers (2)
| | 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»

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

Publication Year: 2017, Page(s):154 - 164
| | PDF (472 KB) | HTML

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»

• ### 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»

• ### Tracking Network Evolution and Their Applications in Structural Network Analysis

Publication Year: 2018, Page(s): 1
| | PDF (3680 KB)

Structural network analysis, including node ranking, community detection and link prediction, has received a lot of attention lately. In the literature, most works focused on structural analysis of a single network. In this paper, we are particularly interested in how the network structure evolves over time. For this, we propose a general framework to track, model, and predict the dynamic network ... View full abstract»

• ### Towards Green Wireless Networking: Fading-Resistant Time Constraint Broadcasts Using Cooperative Communication

Publication Year: 2018, Page(s): 1
| | PDF (36981 KB)

Cooperative broadcast, in which receivers are allowed to combine received packets from different senders to combat transmission errors, has gained increasing attention. Previous studies showed that broadcast optimization solutions are sufficient in non-fading environments but may suffer a low delivery ratio under wireless channel fading. Although some previous works analyze the tradeoff between en... View full abstract»

• ### Moment-Based Spectral Analysis of Random Graphs with Given Expected Degrees

Publication Year: 2017, Page(s):215 - 228
| | PDF (505 KB) | HTML

We analyze the eigenvalues of a random graph ensemble, proposed by Chung and Lu, in which a given sequence of expected degrees, denoted by $overline{w}_n = (w^{(n)}_1,ldots, w^{(n)}_n)$ , is prescribed on the 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 Test of Hypotheses for Random Graph Distributions Built from EEG Data

Publication Year: 2017, Page(s):75 - 82
| | PDF (571 KB) | HTML

The theory of random graphs has been applied in recent years to model neural interactions in the brain. While the probabilistic properties of random graphs has been extensively studied, the development of statistical inference methods for this class of objects has received less attention. In this work we propose a non-parametric test of hypotheses to test if a sample of random graphs was generated... View full abstract»

• ### Data Clustering and Graph Partitioning via Simulated Mixing

Publication Year: 2018, Page(s): 1
| | PDF (1407 KB) |  Media

Spectral clustering approaches have led to well-accepted algorithms for finding accurate clusters in a given dataset. However, their application to large-scale datasets has been hindered by computational complexity of eigenvalue decompositions. Several algorithms have been proposed in the recent past to accelerate spectral clustering, however they compromise on the accuracy of the spectral cluster... 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