# IEEE Transactions on Network Science and Engineering

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

Publication Year: 2018, Page(s): 1
Cited by:  Papers (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»

• ### A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept

Publication Year: 2018, Page(s):261 - 275
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A Self-Organising Cloud Radio Access Network (C-RAN) is proposed, which dynamically adapt to varying capacity demands. The Base Band Units and Remote Radio Heads are scaled semi-statically based on the concept of cell differentiation and integration (CDI) while a dynamic load balancing is formulated as an integer-based optimisation problem with constraints. A Discrete Particle Swarm Optimisation (... View full abstract»

• ### Trust-based Social Networks with Computing, Caching and Communications: A Deep Reinforcement Learning Approach

Publication Year: 2018, Page(s): 1
| | PDF (1707 KB)

Social networks have continuously been expanding and trying to be innovative. The recent advances of computing, caching, and communication (3C) can have significant impacts on mobile social networks (MSNs). MSNs can leverage these new paradigms to provide a new mechanism for users to share resources (e.g., information, computation-based services). In this paper, we exploit the intrinsic nature of ... View full abstract»

• ### Spreading Processes in Multilayer Networks

Publication Year: 2015, Page(s):65 - 83
Cited by:  Papers (61)
| | 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»

• ### Minimizing Social Cost of Vaccinating Network SIS Epidemics

Publication Year: 2018, Page(s):326 - 335
Cited by:  Papers (2)
| | PDF (1008 KB) | HTML

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»

• ### Belief Dynamics in Social Networks: A Fluid-Based Analysis

Publication Year: 2018, Page(s):276 - 287
| | PDF (668 KB) | HTML Media

The advent and proliferation of social media have led to the development of mathematical models describing the evolution of beliefs/opinions in an ecosystem composed of socially interacting users. The goal is to gain insights into collective dominant social beliefs and into the impact of different components of the system, such as users’ interactions, while being able to predict users’ opinions. F... View full abstract»

• ### Finite-Time Passivity of Coupled Neural Networks with Multiple Weights

Publication Year: 2018, Page(s):184 - 197
Cited by:  Papers (2)
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This paper respectively studies finite-time passivity of multi-weighted coupled neural networks (MWCNNs) with and without coupling delays. First, based on those existing passivity definitions, several new concepts about finite-time passivity are presented. By exploiting these definitions of finite-time passivity and designing appropriate controllers, we investigate the passivity of MWCNNs with and... View full abstract»

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

Publication Year: 2018, Page(s): 1
Cited by:  Papers (2)
| | 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»

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

Publication Year: 2017, Page(s):13 - 26
Cited by:  Papers (5)
| | 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»

• ### Cascading Edge Failures: A Dynamic Network Process

Publication Year: 2018, Page(s):288 - 300
| | PDF (898 KB) | HTML

This paper studies a network process that can 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/link$(i,j)$ View full abstract»

• ### Towards Workload Balancing in Fog Computing Empowered IoT

Publication Year: 2018, Page(s): 1
| | PDF (2348 KB)

As latency is the key performance metric for IoT applications, fog nodes co-located with cellular base stations can move the computing resources close to IoT devices. Therefore, data flows of IoT devices can be offloaded to fog nodes in their proximity, instead of the remote cloud, for processing. However, the latency of data flows in IoT devices consist of both the communications latency and comp... View full abstract»

• ### Modelling Spreading Process Induced by Agent Mobility in Complex Networks

Publication Year: 2018, Page(s):336 - 349
| | PDF (1479 KB) | HTML

Most conventional epidemic models assume contact-based contagion process. We depart from this assumption and study epidemic spreading process in networks caused by agents acting as carrier of infection. These agents traverse from origins to destinations following specific paths in a network and in the process, infecting the sites they travel across. We focus our work on theSusceptible-Infe... View full abstract»

• ### Isomorphisms in Multilayer Networks

Publication Year: 2018, Page(s):198 - 211
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We extend the concept of graph isomorphisms to multilayer networks with any number of “aspects” (i.e., types of layering). In developing this generalization, we identify multiple types of isomorphisms. For example, in multilayer networks with a single aspect, permuting vertex labels, layer labels, and both vertex labels and layer labels each yield different isomorphism relations between multilayer... View full abstract»

• ### Core Percolation in Interdependent Networks

Publication Year: 2018, Page(s): 1
| | PDF (3202 KB)

Core percolation, as a fundamental structural transition resulting from preserving core nodes in the network, is crucial in the network controllability and robustness. Prior art has investigated single, non-interacting complex networks where core structure plays an important role in ensuring the network robustness. In contrast, real networks are usually composed of multiple interdependent layers. ... View full abstract»

• ### Deep Convolutional Neural Networks for Indoor Localization with CSI Images

Publication Year: 2018, Page(s): 1
| | PDF (1091 KB)

With the increasing demand of location-based services, Wi-Fi based localization has attracted great interest because it provides ubiquitous access in indoor environments. In this paper, we propose CiFi, deep convolutional neural networks (DCNN) for indoor localization with commodity 5GHz WiFi. First, by leveraging a modified device driver, we can extract phase data of channel state information (CS... View full abstract»

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

Publication Year: 2018, Page(s):2 - 13
Cited by:  Papers (2)
| | 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»

• ### Topology identification in two-layer complex dynamical networks

Publication Year: 2018, Page(s): 1
| | PDF (4134 KB)

This study focuses on topology identification in two-layer networks with peer-to-peer unidirectional couplings, where one layer (the response layer) receives information from the other layer (the drive layer). The goal is to construct a theoretical framework for identifying the topology of the response layer based on the dynamics observed in both layers. In particular, an auxiliary layer is constr... View full abstract»

• ### Stochastic Blockchain for IoT Data Integrity

Publication Year: 2018, Page(s): 1
| | PDF (1584 KB)

This paper proposes a blockchain-based data checking scheme to protect data integrity in Internet of Things (IoT). Traditional data integrity schemes such as symmetric key approaches and public key infrastructure (PKI) suffer from the single-point of failure and network congestion due to the centralized architecture. Motivated by the distributed data authentication in blockchain, we propose to ado... View full abstract»

• ### Centrality measures for graphons: Accounting for uncertainty in networks

Publication Year: 2018, Page(s): 1
| | PDF (8522 KB) |  Media

As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally and conceptually challenging. In particular, node centrality measures rely on the assumption that the graph is perfectly known --- a premise not necessarily fulfilled for large, uncertain networks. Accordingly, centralit... View full abstract»

• ### Learning-Based Dynamic Resource Provisioning for Network Slicing with Ensured End-to-End Performance Bound

Publication Year: 2018, Page(s): 1
| | PDF (1544 KB)

To accommodate different sets of network functions with different quality-of-service requirements for different types of applications in 5G networks, network slicing, which dynamically creates virtual networks, was proposed in the literature and IETF. A critical issue for network slicing is to determine the amount of resources for a network slice to ensure the quality-of-service requirement, and a... View full abstract»

• ### A novel class of distributed fixed-time consensus protocols for second-order nonlinear and disturbed multi-agent systems

Publication Year: 2018, Page(s): 1
| | PDF (1990 KB)

The fixed-time consensus problem is considered in this paper for second-order multi-agent systems (MASs) with inherent nonlinear dynamics and disturbances under a detail-balanced network in both leaderless and leader-following cases. The fixed-time consensus means that MASs reach consensus in finite time and the settling time is uniformly bounded with respect to initial states. Based on the bi-lim... View full abstract»

• ### Design and Analysis of Probing Route to Defense Sink-hole Attacks for Internet of Things Security

Publication Year: 2018, Page(s): 1
| | PDF (1610 KB)

In this paper, a Probe Route based Defense Sinkhole Attack (PRDSA) scheme is proposed to resist Sinkhole attack and guarantee security for IoT, which is the first work that can detect, bypass and locate the sinkhole at the same time. The PRDSA scheme proposes a routing mechanism combining the far-sink reverse routing, equal-hop routing, and minimum hop routing, which can effectively circumvent the... View full abstract»

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

Publication Year: 2018, Page(s): 1
Cited by:  Papers (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»

• ### Provision of Public Goods on Networks: On Existence, Uniqueness, and Centralities

Publication Year: 2018, Page(s):225 - 236
Cited by:  Papers (1)
| | PDF (443 KB) | HTML

We consider the provision of public goods on networks of strategic agents. We study different effort outcomes of these network games, namely, the Nash equilibria, Pareto efficient effort profiles, and semi-cooperative equilibria (resulting from interactions among coalitions of agents). We identify necessary and sufficient conditions on the structure of the network for the uniqueness of the Nash eq... View full abstract»

• ### Modeling communication processes in the human connectome through cooperative learning

Publication Year: 2018, Page(s): 1
| | PDF (5462 KB)

Communication processes within the human brain at different cognitive states are neither well understood nor completely characterized. We assess communication processes in the human connectome using ant colony-inspired cooperative learning algorithm, starting from a source with no a priori information about the network topology, and cooperatively searching for the target through a pheromone-inspir... 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