# IEEE Transactions on Network Science and Engineering

### Early Access Articles

Early Access articles are made available in advance of the final electronic or print versions. Early Access articles are peer reviewed but may not be fully edited. They are fully citable from the moment they appear in IEEE Xplore.

## Filter Results

Displaying Results 1 - 25 of 69
• ### Multiplex Conductance and Gossip Based Information Spreading in Multiplex Networks

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

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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### Mixing Times and Structural Inference for Bernoulli Autoregressive Processes

Publication Year: 2018, Page(s): 1
| | PDF (1381 KB)

We introduce a multivariate random process producing Bernoulli outputs per dimension, that can possibly formalize binary interactions in various graphical structures and can be used to model opinion dynamics, epidemics, financial and biological time series data, etc. We call this a Bernoulli Autoregressive Process (BAR). While many dynamical models of processes on graphs have been studied previous... View full abstract»

• ### 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 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»

• ### 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»

• ### 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»

• ### 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»

• ### The Edge Cover Probability Polynomial of a Graph and Optimal Network Construction

Publication Year: 2018, Page(s): 1
| | PDF (487 KB)

Given a uniform probability $rho, 0 < rho < 1$, of selecting edges independently from a graph $G$, we define the edge cover probability polynomial $Ep(G, rho)$ of $G$ to be the probability of randomly selecting an edge cover of $G$. We provide ... 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»

• ### 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»

• ### Controlling Best Response Dynamics for Network Games

Publication Year: 2018, Page(s): 1
| | PDF (2518 KB)

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»

• ### 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»

• ### 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»

• ### Cultural Structures of Knowledge from Wikipedia Networks of First Links

Publication Year: 2018, Page(s): 1
| | PDF (2220 KB) |  Media

Knowledge is useless without structure. While the classification of knowledge has been an enduring philosophical enterprise, it recently found applications in computer science, notably for artificial intelligence. The availability of large databases allowed for complex ontologies to be built automatically, for example by extracting structured content from Wikipedia. However, this approach is subje... View full abstract»

• ### Secure Overlay Routing for Large Scale Networks

Publication Year: 2018, Page(s): 1
| | PDF (2935 KB)

Probabilistic key pre-distribution schemes have recently emerged as major tools of addressing secure routing challenge in wireless networks. In our previous work, we propose an algorithm capable of finding optimal secure paths in overlay wireless networks. An important concern related to that algorithm is the scalability of the solution for large scale networks containing thousands of nodes. In th... View full abstract»

• ### A Model for Growth of Markets of Products or Services Having Hierarchical Dependence

Publication Year: 2018, Page(s): 1
| | PDF (1056 KB)

Many products and services can only achieve their intended functions and performance when being used in conjunction with or under the operation of other products and services. Such products and services, having varying degrees of hierarchical dependence, are becoming dominant in the global market. This trend has intensified as a result of the rapid growth in the use of networked technology, and is... 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