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Guest Editorial Introduction to the Special Section on Cognitive Software Defined Networks and Applications IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-31
The papers in this special section focus on cognitive software defined networks and applications. Next generation networks (NGNs) are xpected to utilize internal and external sources of data through information and wireless communication techniques. Particularly, the demand for autonomic network management, orchestrations and optimization is as intense as ever, even though significant research has
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Table of Contents IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-30
Presents the table of contents for this issue of the publication.
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Guest Editorial: Introduction to the Special Section on Data-Driven IoT for Smart Cities IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-31
The papers in this special section focus on data-driven Internet of Things (IoT) for smart cities. Developing smart cities to better support the growing urban population is a global and complex challenge and involves interdisciplinary fields. Instead of the traditional Internet of Contents in human-to-human and human-to-machine communications, the Internet of Things with communications among massive
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Guest Editorial: Introduction to the Special Section on Edge Computing for Internet of Things IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-31
The papers in this special section focus on edge computing for Internet of Things (IoT). The IoT is expected to improve the quality of human lives through billions of Internet-based devices that connect the physical and digital worlds. To satisfy the computation and storage requirements of IoT, cloud computing has served as the most important computing infrastructure. However, with the explosion of
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Guest Editorial: Introduction to the Special Section on Heterogeneous Communications Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-31
The papers in this special section focus on heterogeneous communication networks. These networks, consisting of terrestrial mobile networks, satellite networks, IoT, WiFi, and etc., is a promising technique to meet the challenges in future mobile communications. Heterogeneous network resources are expected to cooperate with each other to support more efficient data transmissions and also provide more
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Guest Editorial: Introduction to Special Section on Smart Systems and Intelligent Networking Powered With Big Data Analytics IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-12-31
The papers in this special section focus on smart systems and intelligent networking that is powered with Big Data analytics. Smart systems, including Internet of Things (IoT), have emerged to address contemporary economic, societal, and environmental challenges, such as business and production automation, urban sustainability, climate change, healthcare, and globalization. They encompass different
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Unsupervised Anomaly Detection in IoT Systems for Smart Cities IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-29 Yifan Guo; Tianxi Ji; Qianlong Wang; Lixing Yu; Geyong Min; Pan Li
Anomaly detection is critical in the Internet of Things (IoT) systems due to its wide applications for building smart cities, such as quality control in manufacturing, intrusion detection in system security, fault detection in system monitoring. Many existing schemes are problem specific and supervised approaches, which require domain knowledge and tremendous data labeling efforts. In this paper, we
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A Time-Dependent SIR Model for COVID-19 With Undetectable Infected Persons IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-18 Yi-Cheng Chen; Ping-En Lu; Cheng-Shang Chang; Tzu-Hsuan Liu
In this paper, we conduct mathematical and numerical analyses for COVID-19. To predict the trend of COVID-19, we propose a time-dependent SIR model that tracks the transmission and recovering rate at time $t$ . Using the data provided by China authority, we show our one-day prediction errors are almost less than $3\%$ . The turning point and the total number of confirmed cases in China are predicted
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Maximum Value Matters: Finding Hot Topics in Scholarly Fields IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-07 Guie Meng; Jiasheng Xu; Jinghao Zhao; Luoyi Fu; Huan Long; Xiaoying Gan; Xinbing Wang
Finding hot topics in scholarly fields can help researchers to keep up with the latest concepts, trends, and inventions in their field of interest. Due to the rarity of complete large-scale scholarly data, earlier studies target this problem based on manual topic extraction from a limited number of domains, with their focus solely on a single feature such as coauthorship, citation relations, and etc
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Interdependent Patterns in Protein-Protein Interaction Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-07 Peng Gang Sun; Yining Quan; Qiguang Miao
This paper introduces a new pattern, called interdependent patterns consisting of genes that are closely interdependent in the information transmission process on protein-protein interaction (PPI) networks. Firstly, information flow starts to broadcast from activated genes to any other genes through the shortest paths, in which information is processed, and retransmitted by the genes adhering to the
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Joint Computation Offloading and Scheduling Optimization of IoT Applications in Fog Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-07 Abhishek Hazra; Mainak Adhikari; Tarachand Amgoth; Satish Narayana Srirama
In recent times, fog computing becomes an emerging technology that can exhilarate the cloud services towards the network edge for increasing the speeds up of various Internet-of-Things (IoT) applications. In this context, integrating priority-aware scheduling and data offloading allow the service providers to efficiently handle a large number of real-time IoT applications and enhance the capability
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Table of Contents IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-09-01
Presents the table of contents for this issue of the publication.
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Cache Selection in Dynamic D2D Multicast Networks Using Inhomogeneous Markov Model IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-25 Mansi Peer; Vivek Ashok Bohara; Anand Srivastava
This article presents a user spatio-temporal behavior aware cache selection framework to facilitate device-to-device multicast (D2MD) communication that minimizes the number of caches required while achieving a desired user load on the cellular network. Consequently, it alleviates the caching load on the cellular network. The optimization problem formulated to minimize the number of caches is combinatorial
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Distributed Reinforcement Learning for Cyber-Physical System With Multiple Remote State Estimation Under DoS Attacker IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-24 Pengcheng Dai; Wenwu Yu; He Wang; Guanghui Wen; Yuezu Lv
In this paper, we consider cyber-physical system (CPS) with multiple remote state estimation under denial-of-service (DoS) attack in infinite time-horizon. The sensors monitor the system and send their local state estimate to remote estimators by choosing the local channels in “State 0” or “State 1”. The aim of sensors is to find policies for choosing local channel in a specific state to transmit message
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Structural Balance Preserving and Bipartite Static Consensus of Heterogeneous Agents in Cooperation-Competition Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-24 Hong-Xiang Hu; Guanghui Wen; Guang Chen; Xinghuo Yu; Tingwen Huang
The structural balance preserving problem is studied in this article for heterogeneous agents in the state-dependent cooperation-competition network. The heterogeneous agents considered are described by second-order integrator systems with different intrinsic nonlinear dynamics, and velocity damping terms, and the initial network is structurally balanced, and connected, which can be divided into two
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Network Structure Transmission With Limited Data via Compressed Sensing IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-21 Zhao-Long Hu; Xiao Han; Lijia Ma
Complex networks, formed by nodes and links contain a significant amount of crucial information that can reflect the nature of the systems. In this paper, we propose a network-structure-transmission (NST) framework based on $k$ -shell decomposition and compressed sensing for transmitting network structures and spectral properties with limited data. Specifically, we reduce the average degree and degree
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Transaction Throughput Provisioning Technique for Blockchain-Based Industrial IoT Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-19 Fuad Shamieh; Xianbin Wang; Ahmed Refaey Hussein
The proliferation of the IoT in connected society is rapidly expanding into vertical industry sectors due to the ever-increasing ties amongst businesses and economies. As the number of IoT nodes utilized in a network increases, decentralized network infrastructure, and security provisioning mechanisms, primarily enabled by blockchain-based technologies, become more beneficial. However, blockchain-based
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RL-Routing: An SDN Routing Algorithm Based on Deep Reinforcement Learning IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-19 Yi-Ren Chen; Amir Rezapour; Wen-Guey Tzeng; Shi-Chun Tsai
Communication networks are difficult to model and predict because they have become very sophisticated and dynamic. We develop a reinforcement learning routing algorithm (RL-Routing) to solve a traffic engineering (TE) problem of SDN in terms of throughput and delay. RL-Routing solves the TE problem via experience, instead of building an accurate mathematical model. We consider comprehensive network
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Performance of Bitcoin Network With Synchronizing Nodes and a Mix of Regular and Compact Blocks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-18 Jelena Mišić; Vojislav B. Mišić; Xiaolin Chang
Compact blocks, and compact block protocol are a recent addition to the Bitcoin (BTC) data propagation protocol that aims to reduce bandwidth requirements and, possibly, reduce latency as well. In this work we evaluate operation of BTC network under a mix of regular, and compact block traffic, assuming that nodes randomly leave, and re-join the network, and perform block and, optionally, transaction
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Observer-Based Dynamic Event-Triggered Strategies for Leader-Following Consensus of Multi-Agent Systems With Disturbances IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-18 Xiaoli Ruan; Jianwen Feng; Chen Xu; Jingyi Wang
This paper studies leader-following bounded consensus problem for linear multi-agent systems (MASs) with exogenous disturbances under an observer-based dynamic event-triggered scheme. To guarantee performance requirements, and avoid frequent updates of the sensors, and the controllers at the same time, two independent event-triggered schemes with dynamic threshold are proposed in sensor-to-observer
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Distance Dependent Competitive Interactions in a Frustrated Network of Mobile Agents IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-18 Sayantan Nag Chowdhury; Soumen Majhi; Dibakar Ghosh
Diverse collective dynamics emerge in dynamical systems interacting on top of complex network architectures. Along this line of research, temporal network has come out to be one of the most promising network platforms to investigate. Especially, such network with spatially moving agents has been established to be capable of modelling a number of practical instances. In this paper, we examine the dynamical
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The +1 Method: Model-Free Adaptive Repositioning Policies for Robotic Multi-Agent Systems IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-18 Claudio Ruch; Joel Gächter; Jan Hakenberg; Emilio Frazzoli
Robotic multi-agent systems can efficiently handle spatially distributed tasks in dynamic environments. Problem instances of particular interest, and generality are the dynamic traveling repairman problem, and the dynamic vehicle routing problem. Operational policies for robotic fleets solving these two problems take decisions in an online setting with continuously arriving demands to optimize service
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Reward Optimization for Content Providers With Mobile Data Subsidization: A Hierarchical Game Approach IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-17 Zehui Xiong; Jun Zhao; Dusit Niyato; Ruilong Deng; Junshan Zhang
Mobile data subsidization launched by mobile network operators is a promising business model to provide economic benefits for the mobile data market and beyond. It allows content providers to partly subsidize mobile data consumption of mobile users in exchange for displaying a certain amount of advertisements. From a content provider perspective, it is of great interest to determine the optimal strategy
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Big Data on the Fly: UAV-Mounted Mobile Edge Computing for Disaster Management IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-13 Jianwen Xu; Kaoru Ota; Mianxiong Dong
After disasters, network communication is highly susceptible to disruption. In this case, we may need solutions without original architectures to meet the requirements of connectivity and communication. As a research hotspot, existing studies and practices in disaster management are often costly and may have to rely on differentiated strategies to deal with actual situations. In this paper, we choose
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On Robustness Paradox in Air Traffic Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-13 Qing Cai; Sameer Alam; Vu Duong
Air traffic is operated in an air traffic network (ATN) environment. It is pertinent to improve the robustness of ATNs as they are frequently exposed to manifold uncertainties which can break down their functioning components. Existing studies improve the robustness of an ATN by either rewiring its links or adding more ones. In this paper we discover the robustness paradox phenomenon in ATNs. Specifically
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Federated Region-Learning for Environment Sensing in Edge Computing System IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-12 Yujia Gao; Liang Liu; Binxuan Hu; Tianzi Lei; Huadong Ma
In the last decades, environmental pollution has grown up to be a major problem that influences people's health. Providing accurate environmental sensing services is of great significance. To realize environmental sensing, distributed monitoring sites are used to collect comprehensive long-term environmental data. However, sparse sensory data caused by insufficient monitoring sites and their incomplete
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Multi-Layer Radio Network Slicing for Heterogeneous Communication Systems IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-12 Jingzhi Hu; Zijie Zheng; Boya Di; Lingyang Song
In this paper, we consider the radio access network (RAN) slicing in heterogeneous communication systems. Typically, the infrastructure provider (InP) allocates the radio resources to the mobile virtual network operators (MVNOs) as RAN slices, and then the MVNOs use the allocated resources to provide services for their users. As the RAN being heterogeneous, the users are generally with different quality
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Distributed Adaptive Fault-Tolerant Consensus of Nonlinear Multi-Agent Systems via State-Constraint Impulsive Protocols With Time-Delay IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-12 Can Ke; Chuandong Li; Qiangqiang Zhang
This paper focuses on the distributed adaptive fault-tolerant consensus problem for nonlinear multi-agent systems(MASs) using state-constraint impulsive protocols with time-delay. Firstly, the distributed adaptive online updating schemes based on the local communication among neighboring agents are applied to some adaptive parameters. Secondly, the impulsive control protocols are introduced to save
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Enhanced Online Q-Learning Scheme for Resource Allocation with Maximum Utility and Fairness in Edge-IoT Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-11 Ismail AlQerm; Jianli Pan
Internet of Things (IoT) is experiencing an explosion in the data traffic due to the increase in the number of heterogeneous applications. The existing cloud computing models will not be capable to support the IoT applications that are delay-sensitive and using high bandwidth. The Edge-IoT systems represented by shared edge clouds support a wide range of IoT applications. Edge clouds provide resources
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Influence Diffusion in Online Social Networks With Propagation Rate Changes IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-11 Tianyi Pan; Xiang Li; Alan Kuhnle; My T. Thai
Information can propagate among Online Social Network (OSN) users at a high speed, which makes the OSNs important platforms for viral marketing. Although the viral marketing related problems in OSNs have been extensively studied in the past decade, the existing works all assume known propagation rates. In this paper, we propose a novel model, Dynamic Influence Propagation (DIP), which allows propagation
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Abnormal Crowd Traffic Detection for Crowdsourced Indoor Positioning in Heterogeneous Communications Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-05 Weiwei Li; Zhou Su; Ruidong Li; Kuan Zhang; Qichao Xu
WiFi fingerprint-based indoor positioning system emerges to provide fundamental location-related service in heterogeneous communications networks. It relies on crowdsourcing technology in the collection of received signal strength (RSS) to dynamically update fingerprint database. However, this crowdsourced indoor positioning system is vulnerable to the intrusion of dishonest users (i.e., attackers)
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Defending Malicious Check-In Using Big Data Analysis of Indoor Positioning System: An Access Point Selection Approach IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-05 Weiwei Li; Zhou Su; Kuan Zhang; Abderrahim Benslimane; Dongfeng Fang
The integration of WiFi fingerprint-based indoor positioning technology and big data analysis emerges as a new research prospect. Through the analysis of big data collected from users’ submission, we can discover many other applications of fingerprint positioning. A popular application is the check-in to point of interest (POI) for its crowd traffic evaluation according to the volume of received signal
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Traffic-Aware Rate Adaptation for Improving Time-Varying QoE Factors in Mobile Video Streaming IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-04 Ailing Xiao; Xiaofu Huang; Sheng Wu; Haoting Chen; Li Ma
Mobile video has become one of the most valuable services in next-generation heterogeneous networks, and users’ quality of experience (QoE) is recognized as its important performance metric. In this paper, we propose an adaptive bitrate (ABR) algorithm to achieve improvement of the timevarying QoE determinants during a mobile video playback. Since watching videos will bring mobile data charges to the
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Scaling of Average Shortest Distance of Two Colored Substitution Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-04 Fang Huang; Meifeng Dai; Jie Zhu; Weiyi Su
In this paper, two colored substitution networks by substitution rules are introduced. In order to calculate the sum of all shortest distances, we discuss the following both cases: two nodes are in adjacent branches or non-adjacent ones. The most difficult problem is to compute the sum of all shortest distances whose nodes are in two symmetrical branches. We were very surprised to find one efficient
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Finite-Time Fuzzy Adaptive Consensus for Heterogeneous Nonlinear Multi-Agent Systems IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-08-03 Duxin Chen; Xiaolu Liu; Wenwu Yu
This paper deals with the finite-time consensus control problem for a class of nonlinear strict-feedback multi-agent systems with heterogeneous dynamics. Due to the existence of unknown nonlinear dynamics of the system, this paper adopts the excellent approximation ability of fuzzy logic systems to design the consensus control protocol. Moreover, fuzzy logic systems and adaptive method are used to
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Good or Mediocre? A Deep Reinforcement Learning Approach for Taxi Revenue Efficiency Optimization IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-30 Haotian Wang; Huigui Rong; Qun Zhang; Daibo Liu; Chunhua Hu; Yupeng Hu
Recently, with the rapid expansion of cities, optimizing taxi driving routes for improving taxi revenue efficiency has become the core issue of taxi system. However, most current research focuses on increasing platform revenue instead of improving drivers’ revenue in a centralized dispatch taxi system just like DiDi, which results in a slower driver income growth and greater difficulties for recruiting
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Identification of Generalized Semantic Communities in Large Social Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-27 Di Jin; Xiaobao Wang; Mengquan Liu; Jianguo Wei; Wenhuan Lu; Francoise Fogelman-Soulié
Community detection in networks is a fundamental data analysis task. Recently, researchers have tried to improve its performance by exploiting semantic contents and interpret the communities. However, they typically assume that communities are assortative (i.e. vertices are mostly connected to others within the group), thus they cannot find the generalized community structures, which includes assortative
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Stability of TCP/AQM Networks Under DDoS Attacks With Design IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-27 Liansheng Tan; Kaijiao Huang; Gang Peng; Guanrong Chen
The current Internet is dramatically suffering the Distributed Denial of Service (DDoS) attacks, in which the perpetrator maliciously makes network resource unavailable to its intended users by temporarily or indefinitely disrupting the services of a host connected to the Internet. In this paper, we investigate an Internet transmission control protocol/active queue management (TCP/AQM) router subject
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Hide and Seek: A Markov-Based Defense Strategy Against Off-Sensing Attack in Cognitive Radio Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-24 Moinul Hossain; Jiang Xie
In a cognitive radio-based network (CRN), secondary users (SUs) opportunistically access underutilized spectrum resources and stop utilizing these resources when licensed or primary users (PUs) reappear. However, this way of opportunistic spectrum access is susceptible to novel vulnerabilities. Recently, a new attack, off-sensing (OS), has shed light on a vulnerability in the Federal Communications
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Sequential Recovery of Complex Networks Suffering From Cascading Failure Blackouts IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-22 Jiajing Wu; Zhenhao Chen; Yihan Zhang; Yongxiang Xia; Xi Chen
Over the past decades, prevention and mitigation against cascading failure blackouts in complex networked systems have been extensively studied. In reality, the functional and structural restoration of complex networks suffering from large-scale cascading failures may involve a sequence of repairing actions. In this paper, we propose a novel sequential recovery model that takes into consideration both
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Performance Analysis of Heterogeneous Networks With Wireless Caching and Full Duplex Relaying IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-21 Yingyang Chen; Li Wang; Ruqiu Ma; Weiping Liu; Miaowen Wen; Aiguo Fei
Heterogeneous networks (HetNets) provide a powerful approach to cope with the dramatic mobile traffic growth. However, the backhaul limitation is an essential challenge. This paper is motivated to study how wireless caching and full duplex (FD) relaying can address the aforementioned challenge in a two-tier HetNet. Specifically, we propose a hybrid caching model consisting of probabilistic caching
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Achieving High Throughput for Heterogeneous Networks With Consecutive Caching and Adaptive Retrieval IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-21 Ruidong Li; Kazuhisa Matsuzono; Hitoshi Asaeda; Xiaoming Fu
Heterogeneous networks raise the challenge on ubiquitous connections among heterogeneous devices and networking protocols. As a promising approach to meet this challenge, Information-centric networking (ICN) offers a new communication paradigm which can conceal the heterogeneity of underlying networks. However, it suffers from the problem of segmented cached chunks, which results in low throughput
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A Big Data-Enabled Hierarchical Framework for Traffic Classification IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-16 Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Valerio Persico; Antonio Pescapé
According to the critical requirements of the Internet, a wide range of privacy-preserving technologies are available, e.g. proxy sites, virtual private networks, and anonymity tools. Such mechanisms are challenged by traffic-classification endeavors which are crucial for network-management tasks and have recently become a milestone in their privacy-degree assessment, both from attacker and designer
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On Enumeration of Spanning Arborescences and Reliability for Network Broadcast in Fixed-Schedule Dynamic Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-15 Gaurav Khanna; Sieteng Soh; Sanjay K. Chaturvedi; Kwan-Wu Chin
This paper considers broadcast communications or information dissemination in Fixed-Schedule Dynamic Networks (FSDNs). It shows that the notion of spanning arborescences, commonly used in static networks, is not applicable in FSDNs. This paper then introduces two new concepts on spanning arborescences: (i) ${\boldsymbol{t}}$ -arborescence – an arborescence in which all edges have contact schedules
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From Spectra to Localized Networks: A Reverse Engineering Approach IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-14 Priodyuti Pradhan; Sarika Jalan
Understanding the localization properties of eigenvectors of complex networks is important to get insight into various structural and dynamical properties of the corresponding systems. Here, we analytically develop a scheme to construct a highly localized network for a given set of networks parameters that is the number of nodes and the number of interactions. We find that the localization behavior
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DSCD: Delay Sensitive Cross-Domain Virtual Network Embedding Algorithm IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-10 Peiying Zhang; Xue Pang; Yanxian Bi; Haipeng Yao; Huijiang Pan; Neeraj Kumar
In the coming 5G era, more and more applications are time-delay sensitive, and the importance of low delay in fields such as telemedicine, autonomous driving and military order transmission is self-evident. However, for different application scenarios, their delay requirements are different. How to meet different Quality of service (QoS) requirements simultaneously becomes a challenge. The emergence
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Reprogramming Multistable Monotone Systems With Application to Cell Fate Control IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-09 Rushina Shah; Domitilla Del Vecchio
Multistability is a key property of dynamical systems modeling cellular regulatory networks implicated in cell fate decisions, where, different stable steady states usually represent distinct cell phenotypes. Monotone network motifs are highly represented in these regulatory networks. In this paper, we leverage the properties of monotone dynamical systems to provide theoretical results that guide the
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Many-Objective Deployment Optimization of Edge Devices for 5G Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-09 Bin Cao; Qianyue Wei; Zhihan Lv; Jianwei Zhao; Amit Kumar Singh
Mobile Edge Computing (MEC) and fog computing are the key technologies in fifth generation (5 G) networks. In an MEC system, the data of terminal devices can be processed at the edge nodes also known as fog nodes, which can reduce the data transmission from the terminal devices to the cloud, thus reducing the latency and pressure of network traffic. Due to the huge amount of users’ data, a large number
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Computation-Communication Trade-Offs and Sensor Selection in Real-Time Estimation for Processing Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-09 Luca Ballotta; Luca Schenato; Luca Carlone
Recent advances on hardware accelerators and edge computing are enabling substantial processing to be performed at each node (e.g., robots, sensors) of a networked system. Local processing typically enables data compression and may help mitigate measurement noise, but it is still usually slower compared to a central computer (i.e., it entails a larger computational delay). Moreover, while nodes can
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A Precoding Compensation Scheme for Heterogeneous Communication Networks With CSI Feedback Delay IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-07 Lin Bai; Jiaxing Wang; Rui Han; Dongquan Li; Jianwei Liu; Jinho Choi
In the 5th generation cellular systems, heterogeneous communication networks allow multiple base stations (BSs) to serve the users cooperatively, which can satisfy the requirement of growing data rate and optimum coverage. However, suffering from the imperfect channel state information (CSI) feedback, optimal performance may not be guaranteed for coordinated multiple point (CoMP) scenarios when certain
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Distributed Optimal State Consensus for Multiple Circuit Systems With Disturbance Rejection IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-07 Zhu Wang; Dong Wang; Dongbing Gu
This paper investigates the distributed optimal state consensus problem for an electronic system with a group of circuit units. The dynamics of each unit is modeled by a Chua's circuit in the presence of disturbance generated by an external system. By means of the internal model approach and feedback control, a compensator-based continuous-time algorithm is proposed to minimize the sum of all cost
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Polymorphic Smart Network: An Open, Flexible and Universal Architecture for Future Heterogeneous Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-07-03 Yuxiang Hu; Dan Li; Penghao Sun; Peng Yi; Jiangxing Wu
Burdened with the specialized bearing requirements brought by the deep fusion of the Internet and the economic society, the current Internet is faced with a series of great challenges including intelligence, diversification, personalization, robustness and efficiency because of some defects such as rigid structure, simple bearing structure based on IP, and disability in suppressing unknown threats
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Table of Contents IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-04
Presents the table of contents for this issue of the publication.
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Guest Editorial: Introduction to the Special Section on Economics of Modern Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-04 Jianwei Huang; Costas Courcoubetis; Mihaela Van Der Schaar; Biying Shou; Jean Walrand
The papers in this special section focus on the economics on modern network systems. Many modern networks are becoming increasingly heterogeneous, dynamic, and complex. The need for smart and self-organizing network designs has become a central research issue in a variety of applications and scenarios. Proper economic mechanism design will go hand-in-hand with technology advances in solving many complex
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Guest Editorial Introduction to the Special Section on Network of Cyber-Social Networks: Modeling, Analysis, and Control IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-04 Xiang Li; Ljiljana Trajkovic
The papers in this special section focus on the network of cyber-social networks (NCSN), with particular emphasis on modeling, analysis and control. NCSN is a promising new area that has recently attracted significant interests. Its core differentiator is the tight conjoining among heterogeneous cyber-social networks or between cyber and physical networks. The focus of this special section is to address
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Guest Editorial Introduction to the Special Section on Network Science for High-Confidence Cyber-Physical Systems IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-04 Xiuzhen Cheng; Sriram Chellappan; Wei Cheng; Gokhan Sahin
The papers in this special section focus on network science for high confidence cyber-physical systems (CPS) Here CPS refers to the engineered systems that can seamlessly integrate the physical world with the cyber world via advanced computation and communication capabilities. To enable high-confidence CPS for achieving better benefits as well as supporting emerging applications, network science-based
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Guest Editorial Introduction to the Special Section on Scalability and Privacy in Social Networks IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-04 Donghyun Kim; My T. Thai; R. N. Uma
The papers in this special section focus on scalability and privacy in online social network services. (OSNs) The growing popularity of OSNs and their emerging applications attracted much attention from both academia and industry during recent years. Due to their nature, social networks are considered as sources of Big Data containing large amounts of privacy-sensitive information. A social network
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Deep Learning Based Radio Resource Management in NOMA Networks: User Association, Subchannel and Power Allocation IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-23 Haijun Zhang; Haisen Zhang; Keping Long; George K. Karagiannidis
With the rapid development of future wireless communication, the combination of NOMA technology and millimeter-wave(mmWave) technology has become a research hotspot. The application of NOMA in mmWave heterogeneous networks can meet the diverse needs of users in different applications and scenarios in future communications. In this paper, we propose a machine learning framework to deal with the user
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Dynamic Pricing for Resource-Quota Sharing in Multi-Access Edge Computing IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-17 Marie Siew; Desmond Cai; Lingxiang Li; Tony Q. S. Quek
In this paper, we analyze resource allocation in Multi-Access Edge Computing (MEC) from the perspective of revenue and profit management. Current coarse-grained pricing and resource plans have not made full use of the extreme heterogeneity of computing usage levels across users in the Internet of Everything (IoE), leading to wastage. Some users would have excess un-utilized resource quota while others
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Tensor Entropy for Uniform Hypergraphs IEEE Trans. Netw. Sci. Eng. (IF 5.213) Pub Date : 2020-06-16 Can Chen; Indika Rajapakse
In this paper, we develop the notion of entropy for uniform hypergraphs via tensor theory. We employ the probability distribution of the generalized singular values, calculated from the higher-order singular value decomposition of the Laplacian tensors, to fit into the Shannon entropy formula. We show that this tensor entropy is an extension of von Neumann entropy for graphs. In addition, we establish