# IEEE Transactions on Network Science and Engineering

## Issue 99

Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE's Preprint or Rapid Post processes. Preprint articles are peer-reviewed but not fully edited. Rapid Post articles are peer-reviewed and edited but not paginated. Both these types of Early Access articles are fully citable from the moment they appear in IEEE Xplore.

## Filter Results

Displaying Results 1 - 25 of 70
• ### Weighted network estimation by the use of topological graph metrics

Publication Year: 2018, Page(s): 1
| | PDF (483 KB)

Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edges and have found applications in many scientific fields. In this work, the use of graph metrics is employed in network estimation by developing optimisation methods that incorporate prior knowledge of a network's... View full abstract»

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

Publication Year: 2018, Page(s): 1
| | PDF (7578 KB)

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»

• ### Robustness of Interdependent Random Geometric Networks

Publication Year: 2018, Page(s): 1
| | PDF (2179 KB)

We propose an interdependent random geometric graph (RGG) model for interdependent networks. Based on this model, we study the robustness of two interdependent spatially embedded networks where interdependence exists between geographically nearby nodes in the two networks. We study the emergence of the giant mutual component in two interdependent RGGs as node densities increase, and define the per... 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

• ### 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»

## 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