# 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»

• ### Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach

Publication Year: 2018, Page(s): 1
| | PDF (6232 KB)

Channel state information (CSI) estimation is one of the most fundamental problems in wireless communication systems. Various methods, so far, have been developed to conduct CSI estimation, which usually requires high computational complexity. However, these methods are not suitable for 5G wireless communications due to many techniques (e.g., massive MIMO, OFDM, and millimeter-Wave (mmWave)) to be... View full abstract»

• ### Redundancy Avoidance for Big Data in Data Centers: A Conventional Neural Network Approach

Publication Year: 2018, Page(s): 1
| | PDF (881 KB)

As the innovative data collection technologies are applying to every aspect of our society, the data volume is skyrocketing. Such phenomenon poses tremendous challenges to data centers with respect to enabling storage. In this paper, a hybrid-stream big data analytics model is proposed to perform multimedia big data analysis. This model contains four procedures, i.e., data pre-processing, data cla... View full abstract»

• ### Efficient Resource Allocation Utilizing Q-Learning in Multiple UA Communications

Publication Year: 2018, Page(s): 1
| | PDF (320 KB)

In recent years, unmanned aircraft systems (UASs) have garnered significant attention, and the demand for communication utilizing unmanned aircrafts (UAs) has increased. However, the limited available frequency for UA communication, despite the increasing utilization, poses a problem. Moreover, for the practical application of UA communication, the changes and differences in the propagation enviro... 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»

• ### 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»

• ### 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»

• ### Cascading Failures in Interdependent Systems: Impact of Degree Variability and Dependence

Publication Year: 2018, Page(s):127 - 140
| | PDF (372 KB) | HTML

We study cascading failures in a system comprising interdependent networks/systems, in which nodes rely on other nodes both in the same system and in other systems to perform their function. The (inter-)dependence among nodes is modeled using a dependence graph, where the degree vector of a node determines the number of other nodes it can potentially cause to fail in each system through aforementi... View full abstract»

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

Publication Year: 2018, Page(s):86 - 91
| | PDF (237 KB) | HTML

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»

• ### Privacy-Preserving Auction for Big Data Trading Using Homomorphic Encryption

Publication Year: 2018, Page(s): 1
| | PDF (818 KB)

Cyber-Physical Systems (smart grid, smart transportation, smart cities, etc.), driven by advances in Internet of Things (IoT) technologies, will provide the infrastructure and integration of smart applications to accelerate the generation and collection of big data to an unprecedented scale. As now a fundamental commodity in our current information age, such big data is a crucial key to competitiv... 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»

• ### A Multi-Objective Evolutionary Algorithm for Promoting the Emergence of Cooperation and Controllable Robustness on Directed Networks

Publication Year: 2018, Page(s):92 - 100
| | PDF (866 KB) | HTML

The directedness of links is of significance in complex networks, and much attention has been paid to study the dynamics of directed networks recently.In networked systems, where the emergence of cooperation and robustness are two hot issues in recent decades. Previous studies have indicated that the structures for promoting these two properties are opposite, which also reveals the great impact of... 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»

• ### 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»

• ### Data-Driven Resource Management for Ultra-Dense Small Cells: An Affinity Propagation Clustering Approach

Publication Year: 2018, Page(s): 1
| | PDF (2680 KB)

Deploying dense small cells is the key to providing high capacity, but raise the serious issue of energy consumption and inter-cell interference. To understand the behaviors of ultra-dense small cells (UDSC) with dynamic interference and traffic patterns, this paper presents a data-driven resource management (DDRM) framework to implement power control and channel rearrangement in UDSC. We find tha... View full abstract»

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

Publication Year: 2018, Page(s):141 - 155
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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' neighborhood that relies on sensory perception and Euclidian space locality is replaced with graph-theoretic network-based proximity mimicking communication and social networks.... View full abstract»

• ### A Robust Advantaged Node Placement Strategy for Sparse Network Graphs

Publication Year: 2018, Page(s):113 - 126
| | PDF (1159 KB) | HTML

Establishing robust connectivity in heterogeneous networks (HetNets) is an important yet challenging problem. For a HetNet accommodating a large number of nodes, establishing perturbation-invulnerable connectivity is of utmost importance. This paper provides a robust advantaged node placement strategy best suited for sparse network graphs. In order to offer connectivity robustness, this paper mode... View full abstract»

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

Publication Year: 2018, Page(s):101 - 112
| | PDF (1041 KB) | HTML 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»

• ### Convergence Analysis of a Distributed Optimization Algorithm with a General Unbalanced Directed Communication Network

Publication Year: 2018, Page(s): 1
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In this paper, we discuss a class of distributed constrained optimization problems in power systems where the target is to optimize the sum of all agents' local convex objective functions over a general unbalanced directed communication network. Each local convex objective function is known exclusively to a single agent, and the agents' variables are constrained to global coupling li... 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»

• ### Preventive and Reactive Cyber Defense Dynamics Is Globally Stable

Publication Year: 2018, Page(s):156 - 170
Cited by:  Papers (1)
| | PDF (1033 KB) | HTML

The recently proposed cybersecurity dynamics approach aims to understand cybersecurity from a holistic perspective by modeling the evolution of the global cybersecurity state. These models describe the interactions between the various kinds of cyber attacks and the various kinds of cyber defenses that take place in complex networks. In this paper, we study a particular kind of cybersecurity dynami... 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### Distributed Link Removal Using Local Estimation of Network Topology

Publication Year: 2018, Page(s): 1
| | PDF (1011 KB) |  Media

This paper considers the problem of network structure manipulation in the absence of information on the global network topology. In particular, the problem of removing some of links is investigated in order to slow or stop the spread of disease in a network while preserving its connectivity. Existing methods solve this combinatorial problem in a centralized manner and they require the global infor... 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»

• ### Will Scale-free Popularity Develop Scale-free Geo-social Networks?

Publication Year: 2018, Page(s): 1
| | PDF (1613 KB) |  Media

Empirical results show that spatial factors such as distance, population density and communication range affect our social activities, also reflected by the development of ties in social networks. This motivates the need for social network models that take these spatial factors into account. Therefore, in this paper we propose a gravity-low-based geo-social network model, where connections develop... 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»

• ### 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»

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

Publication Year: 2018, Page(s): 1
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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»

• ### Robust Network Routing under Cascading Failures

Publication Year: 2014, Page(s):53 - 66
Cited by:  Papers (8)
| | PDF (510 KB) | HTML

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»

• ### Controlling Best Response Dynamics for Network Games

Publication Year: 2018, Page(s): 1
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Controlling networked dynamical systems is a complex endeavor, specifically keeping in mind the fact that in many scenarios the actors that are engaged in the dynamism behave selfishly and therefore only take into account their own individual utility, a setting that has been widely studied in the field of game theory. One way that we can control the system dynamics is through the use of control pa... View full abstract»

• ### Distributed Online Convex Optimization Over Jointly Connected Digraphs

Publication Year: 2014, Page(s):23 - 37
Cited by:  Papers (7)
| | PDF (548 KB) | HTML

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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

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

Publication Year: 2016, Page(s):147 - 158
Cited by:  Papers (1)
| | PDF (483 KB) | HTML 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»

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

Publication Year: 2017, Page(s):187 - 200
| | PDF (1181 KB) | HTML

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»

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

Publication Year: 2017, Page(s):165 - 176
| | PDF (405 KB) | HTML

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
| | 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

Publication Year: 2017, Page(s):129 - 139
| | PDF (696 KB) | HTML Media

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»

## 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