# 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 59
• ### 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 Blockmodels for Inference on Realistic Network Interactions

Publication Year: 2018, Page(s): 1
| | PDF (10342 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

Publication Year: 2018, Page(s): 1
| | PDF (1448 KB)

This paper studies a promising application in Vehicular Cyber-Physical Systems (VCPS) called roadside advertisement dissemination. Its application involves three elements: the drivers in the vehicles, Roadside Access Points (RAPs), and shopkeepers. The shopkeeper wants to attract as many customers as possible by using RAPs to disseminate advertisements to the passing vehicles. Upon receiving an ad... View full abstract»

• ### Influence of Clustering on Cascading Failures in Interdependent Systems

Publication Year: 2018, Page(s): 1
| | PDF (794 KB)

We study the influence of clustering, more specifically triangles, on cascading failures in interdependent networks or systems, in which we model the dependence between comprising systems using a dependence graph. First, we propose a new model that captures how the presence of triangles in the dependence graph alters the manner in which failures transmit from affected systems to others. Unlike exi... 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»

• ### Amplitude Death in Strongly Coupled Polygonal Oscillatory Networks with Sharing Branch

Publication Year: 2018, Page(s): 1
| | PDF (731 KB)

Amplitude changes and amplitude death (AD) are observed in several types of coupled polygonal oscillatory networks that suffer from strong frustration. In this paper, we confirm that the occurrence time of AD depends on the location of the oscillators in the networks. To explain the mechanism of these interesting phenomena, we conduct theoretical analysis by applying the averaging method to the pr... View full abstract»

• ### Node Scheduling and Compressed Sampling for Event Reporting in WSNs

Publication Year: 2018, Page(s): 1
| | PDF (9535 KB)

This work focuses on developing a node scheduling algorithm for detecting events in a sensor field such that few random samples from a set of the active sensor nodes are transmitted to the cluster head and are further used for almost complete reconstruction of the cluster data. A node scheduling algorithm is proposed to achieve maximum coverage of the physical sensor field with correlated sensor r... 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»

• ### Image and Attribute Based Convolutional Neural Network Inference Attacks in Social Networks

Publication Year: 2018, Page(s): 1
| | PDF (3978 KB)

In modern society, social networks play an important role for online users. However, one unignorable problem behind the booming of the services is privacy issues. At the same time, neural networks have been swiftly developed in recent years, and are proven to be very effective in inference attacks. This paper proposes a new framework for inference attacks in social networks, which smartly integrat... View full abstract»

• ### Spectral properties of extended Sierpiński graphs and their applications

Publication Year: 2018, Page(s): 1
| | PDF (834 KB)

The eigenvalues of a graph present a wide range of applications in structural and dynamical aspects of the graph. Determining and analyzing spectra of a graph has been an important and exciting research topic in recent years. In this paper, we study the spectra and their applications for extended Sierpiński graphs, which are closely related to WK-recursive networks that are widely used in t... View full abstract»

• ### Pricing for profit in Internet of Things

Publication Year: 2018, Page(s): 1
| | PDF (4331 KB) |  Media

The economic model of the Internet of Things (IoT) consists of end users, advertisers and three different kinds of providers-IoT service provider (IoTSP), Wireless service provider (WSP) and cloud service provider (CSP). We investigate three different kinds of interactions among the providers. First, we consider that the IoTSP prices a bundled service to the end-users, and the WSP and CSP pay the ... View full abstract»

• ### Graph Theoretical Analysis on Distributed Line Graphs for Peer-to-Peer Networks

Publication Year: 2018, Page(s): 1
| | PDF (3889 KB)

Distributed line graphs were introduced by Zhang and Liu as an overlay for Peer-to-Peer networks. Distributed line graphs have some useful properties as a network topology, such as out-regular and small diameter, where the former implies that each user possesses a constant size of routing table and the latter means that a reasonably small number of hops is necessary to reach a target user. In this... 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