Antenna and Propagation for 5G and Beyond

Submission Deadline: 31 December 2019

IEEE Access invites manuscript submissions in the area of Antenna and Propagation for 5G and Beyond.

5G is not just the next evolution of 4G technology; it’s a paradigm shift. “5G and Beyond” will enable bandwidth in excess of 100s of Mb/s with latency of less than 1 ms, in addition to providing connectivity to billions of devices. The verticals of 5G and beyond are not limited to smart transportation, industrial IoT, eHealth, smart cities, and entertainment services; transforming the way humanity lives, works, and engages with its environment.

“5G and beyond” is an enormous opportunity but the widespread deployment of 5G still faces many challenges, including reliable connectivity, a wide range of bands to support ranging from the 600 MHz UHF band to the mm-wave 60 GHz V-band, dynamic spectrum sharing, channel modeling and wave propagation for ultra-dense wireless networks, as well as price pressures. Besides other required features, the choice of an antenna system will be a critical component of all the node end devices. Choosing the right antenna for an application presents a key design challenge. Creating effective antenna performance requires engineers to examine several factors including antenna size, from what is needed to what is possible, antenna shape, and placement. As consumer electronic modules continue to shrink, incorporating more wireless technologies, making space for antennas is becoming an increasingly significant challenge. Thus, the antenna designers face the restrictions of maintaining reasonable performance in ever-shrinking footprints and under extreme interference conditions. Since high frequency bands are expected to be used in 5G, the propagation characteristics such as propagation loss and multipath characteristics must be evaluated for mm Wave frequencies and beyond. Therefore, new radio propagation modeling and prediction techniques need to be developed to cover the new frequency bands for future 5G wireless systems.

The explosive growth of 5G creates many scientific and engineering challenges that call for ingenious research efforts from both academia and industry. This Special Section in IEEE Access brings together scholars, professors, researchers, engineers, and administrators to find new approaches for exploiting challenging propagation channels and the development of efficient, cost-effective, scalable, and reliable antenna systems/solutions. Further, this Special Section will allow researchers to identify new opportunities for this exciting field.

The topics of interest include, but are not limited to:

  • Massive MIMO Antenna Systems: design and applications
  • Distributed Massive MIMO
  • Smart Reconfigurable Antenna Design and Systems
  • Antenna and propagation for smart wearables IoT
  • Base Station and Terminal Antennas
  • Antennas for Machine to Machine (M2M) Connection
  • mm Wave Antennas
  • Antennas for Terahertz applications
  • Antennas for Driverless Cars
  • Phased Array Antennas
  • Antenna Beamforming
  • Channel enhancement techniques
  • Propagation modeling for 5G
  • Channel modeling and wave propagation for smart cities
  • Electromagnetic wave attenuation and RF signal propagation in smart cities

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Muhammad Ali Imran, University of Glasgow, UK

Guest Editors:

  1. Asimina Kiourti, The Ohio State University, USA
  2. Hassan Tariq Chattha, Islamic University of Madinah, Saudi Arabia
  3. Yejun He, Shenzhen University, China
  4. Akram Alomainy, Queen Mary University of London, UK
  5. Raheel M. Hashmi, Macquarie University, NSW, Australia
  6. Muhammad Zulfiker Alam, Queens University, Kingston, Canada
  7. Qammer H. Abbasi, University of Glasgow, UK

 

Relevant IEEE Access Special Sections:

  1. Millimeter-wave and Terahertz Propagation, Channel Modeling and Applications
  2. 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility
  3. Advances in Statistical Channel Modeling for Future Wireless Communications Networks


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: Muhammad.imran@glasgow.ac.uk; qammer.abbasi@glasgow.ac.uk.

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Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs)

Submission Deadline: 30 November 2019

IEEE Access invites manuscript submissions in the area of Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs).

With rapid economic development, the number of vehicles on the road has grown dramatically, which introduces an array of traffic-related issues, such as traffic congestion and driving safety. Intelligent connected vehicles (ICVs) can provide a safer and greener transportation system, which has been envisioned as an effective measure to resolve traffic problems. ICVs are expected to run many emerging smart applications (e.g., autonomous driving, safety early warning, natural language processing, etc.) to assist both the drivers and passengers in vehicular environments. These kinds of applications typically require significant computing power to perform computation-intensive and latency-sensitive tasks generated by the vehicle sensors for low-latency response. However, the limited computation capacity of the on-board computer makes it difficult to satisfy the computation requirements of quality-of-experience (QoE)-demanding applications. To tackle this challenge, fog/edge computing are proposed as innovative computing paradigms to extend computing capacity to the network edge in order to meet the requirements. Fog/edge computing is expected to not only maximize the computation capability and alleviate the greenhouse effect, but also achieve sustainable operation by pushing rich computing and storage resources to the edge of the network.

The limited computation capacity of the on-board computer brings about an unprecedented challenge for the future development of ICVs. Fog/edge computing provides cloud computing capacity in close proximity to vehicles. Vehicles can migrate the computing to the edge of the network via vehicle to everything (V2X) communication. Processing can be completed at road-side unit (RSU) at the side of the network. The advancement of communication technologies and edge computing, such as Fifth-generation (5G), Software Defined Networking (SDN), Network Function Virtualization (NFV), mobile edge/fog computing and so on, makes it possible to enhance computational capabilities, ensure near-real-time responses and realize communication requirements with ultra-low latency and ultra-high reliability. The Special Section in IEEE Access aims to provide the latest research findings and solutions, in terms of communication and edge computing for ICVs.

The topics of interest include, but are not limited to:

  • New architecture and framework establishment based on fog/edge computing for ICVs
  • Advanced vehicular networks technologies, such as 5G vehicular networks, LTE-V and so on
  • Ultra-reliable and low-latency communications for ICVs
  • Resource allocation and management based on fog/edge computing for ICVs
  • Machine learning, deep learning for intelligent management and control
  • Joint analysis of communication and computing to improve performance in vehicular networks
  • Cross-layer optimization for fog/edge computing
  • Mobility modeling and management for ICVs
  • SDN and NFV technologies for vehicular networks
  • Security and privacy challenges

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Lei Shu, Nanjing Agricultural University, China / University of Lincoln, UK

Guest Editors:

  1. Junhui Zhao, East China Jiaotong University, China / Beijing Jiaotong University, China
  2. Yi Gong, Southern University of Science and Technology, China
  3. Changqing Luo, Virginia Commonwealth University, USA
  4. Tim Gordon, University of Lincoln, UK

 

Relevant IEEE Access Special Sections:

  1. Mobile Edge Computing and Mobile Cloud Computing: Addressing Heterogeneity and Energy Issues of Compute and Network Resources
  2. D2D communications: Security Issues and Resource Allocation
  3. Smart caching, communications, computing and cybersecurity for Information-Centric Internet of Things


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: lei-shu@outlook.com.

Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts

Submission Deadline:  31 August 2019

IEEE Access invites manuscript submissions in the area of Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts.

Smart health big data is paving a promising way for ubiquitous health management, leveraging exciting advances in biomedical engineering technologies, such as convenient bio-sensing, health monitoring, in-home monitoring, biomedical signal processing, data mining, health trend tracking, evidence-based medical decision support etc. To build and utilize the smart health big data, advanced data sensing and data mining technologies are closely-coupled key enabling factors. In smart health big data innovations, challenges arise in how to informatively and robustly build the big data with advanced sensing technologies, and how to automatically and effectively decode patterns from the big data with intelligent computational methods. More specifically, advanced sensing techniques should be able to capture more modalities that can reflect rich physiological and behavioral states of humans, and enhance the signal robustness in daily wearable applications. In addition, intelligent computational techniques are required to unveil patterns deeply hidden in the data, and nonlinearly convert the patterns to high level medical insights.

This Special Section in IEEE Access invites academic and industrial experts to make their contributions to smart health big data, empowered by biomedical sensing and computational intelligence technologies. Studies are expected to connect the human body, data, and applications, establish an end-to-end information flow, and convert big data to big impacts. Crucial technologies include wearable sensing, in-home sensing, personal health record establishment, biomedical signal processing, deep learning, big data mining, pattern recognition, and other related techniques. This Special Section will allow readers to identify advancements, challenges and new opportunities in cutting-edge smart health big data innovations.

The topics of interest include, but are not limited to:

  • Wearable sensing for big data: bio-potential sensing, behavioral sensing, optical sensing, ultrasonic sensing, flexible sensing, emerging wearable imaging, etc.
  • In-home sensing for big data: on-bed sensing, sleep quality sensing, activity sensing, mobility sensing, fall detection, rehabilitation monitoring, etc.
  • Personal health big data: cardiac monitoring, cardiopulmonary monitoring, brain function monitoring, mobility monitoring, life style monitoring, etc.
  • Signal quality enhancement in wearable big data sensing
  • Biomedical signal processing for smart health big data
  • Feature extraction and critical feature selection from smart health big data
  • Automatic feature mining using deep learning from smart health big data
  • Dimension reduction for effective learning from smart health big data
  • Time series, image and unstructured data fusion
  • Data mining from large databases for pattern and correlation finding
  • Knowledge discovery in smart health big data
  • Telemedicine, internet of medical things, mobile health, remote health monitoring
  • Precision medicine exploration based on smart health big data
  • Medical relevant insight learning from long-term health records
  • Real-time health alerts and long-term health trend analytics
  • Sleep quality monitoring and analytics with smart health big data
  • Human-computer interaction for rehabilitation and assisted living
  • Lifestyle changing empowered by digital health technologies
  • Smart health big data to empower clinical trials

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Qingxue Zhang, Indiana University-Purdue University, USA

Guest Editors:

  1. Vincenzo Piuri, University of Milan, Italy
  2. Edward A. Clancy, Worcester Polytechnic Institute, USA
  3. Dian Zhou, University of Texas at Dallas & Fudan University, USA & China
  4. Thomas Penzel, Charite University Hospital, Germany
  5. Walter Hu, University of Texas at Dallas & One-Chip Co., Ltd., USA & China
  6. Hui Zheng, Harvard University & Massachusetts General Hospital, USA

 

Relevant IEEE Access Special Sections:

  1. Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications
  2. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions
  3. Human-Centered Smart Systems and Technologies


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: qxzhang@iu.edu.

Design and Analysis Techniques in Iterative Learning Control

Submission Deadline:  31 July 2019

IEEE Access invites manuscript submissions in the area of Design and Analysis Techniques in Iterative Learning Control.

Recently, great progress has been witnessed in both theory developments and practical applications of iterative learning control (ILC). ILC has been widely used in industry, for example, in chemical processes, robotic manipulators, hard disk drives, milling and laser cutting, traffic flow control systems, and rehabilitation robotic systems. With its rapid development, ILC has also encountered many theoretical and practical challenges including new system applications such as fractional-order systems, new operation environments such as networked structure and complex networks, and new technical innovations such as convergence analysis methods. Therefore, ILC is at a significant stage for making fundamental breakthroughs, which motivates this Special Section in IEEE Access.

Since the proposal of its original concept by Arimoto, et al., in 1984, ILC has developed rapidly over the last three decades. A survey by Bristow, Tharayil, and Alleyne, in IEEE Control Systems provided a comprehensive review of the fundamental framework of ILC and common design and analysis techniques. A comprehensive review was presented in another survey published by Ahn, Chen, and Moore, in IEEE Transactions on Systems, Man, and Cybernetics, Part C, which covered the field from 1998 to 2004. Later surveys reported on other directions of ILC. From these surveys and the references therein, it is observed that the exploration of ILC in various directions has been a mainstream in the past few decades. These explorations have greatly enriched the system of ILC and established the advantages of ILC compared with other traditional control methodologies. However, we are facing a bottleneck in developing ILC due to the lack of current growth.

Scholars in the community have reached a consensus that ILC requires an in-depth review of the past contributions as well as an exciting look at the future directions for ILC. It is necessary to collect fresh ideas from the community to contribute to an understanding of the future developments of ILC. In other words, while exploring ILC for more system and operation conditions, we should also explore the essential advantages of ILC so that we can establish a comprehensive system of ILC. In particular, three major directions should be explored. First, we can apply ILC to new systems, especially newly formed system formulation. This extension can help broaden the potential application range and promote associated research. Second, we should pay attention to new operation environments, especially the emerging conditions. For example, Cyber Physical Systems (CPS) has gained attention from the community; how to implement ILC in CPS is interesting, but security issues should also be considered. Third, we must propose new design and analysis techniques, to carry forward the merits of ILC.

This Special Section in IEEE Access invites original articles addressing both design and analysis techniques in the area of learning control, including novel applications, design frameworks, analysis tools, essential performance improvements, and other related topics in learning control. It aims to provide an in-depth review of the recent advances and a comprehensive outlook of the development trends in learning control.

The topics of interest include, but are not limited to:

  • Learning control for new types of systems
  • Nonlinear design framework of learning control
  • Novel convergence and performance analysis techniques
  • Learning control with new operation conditions
  • New applications
  • Integration with artificial intelligence
  • Big data driven learning control

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Youqing Wang, Shandong University of Science and Technology, China

Guest Editors:

  1. Dong Shen, Beijing University of Chemical Technology, China
  2. Wojciech Paszke, University of Zielona Gora, Poland
  3. YangQuan Chen, University of California, Merced, USA

 

Relevant IEEE Access Special Sections:

  1. Cyber-Physical Systems
  2. Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in Internet of Medical Things
  3. Big Data Learning and Discovery


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: wang.youqing@ieee.org.

Intelligent Data Sensing, Collection and Dissemination in Mobile Computing

Submission Deadline: 15 October 2019

IEEE Access invites manuscript submissions in the area of Intelligent Data Sensing, Collection and Dissemination in Mobile Computing.

With the application of mobile computing, there could be more intelligent ways to sense and collect data, and to reduce the workload of participants. In addition, the scale of data sensing, collection and dissemination could increase. Mobile computing makes full use of various sensing devices, such as smart phones, wireless body sensors, smart sensing devices in manufacturing, and smart meters. These devices, which sense and collect data (on the order of zettabytes in the near future), together with the computing power of mobile devices, develop a new paradigm to data sensing, collection and dissemination. Mobile Computing has emerged as a prospective computing paradigm to pave the way to pervasive computing for mobile and big-data applications.

To ensure intelligent data sensing, data collection and data processing based on mobile computing over the pervasive computing environment, there are some fundamental challenges. Many open issues remain unresolved, such as how to achieve the expected performance for intelligent data sensing, data collection, data processing, and how to ensure the data quality, data reliability, information security and privacy in data collection/dissemination with intelligence. Other relevant aspects should also be studied, such as the computation cost, the platform, tools, service discovery, data management, and analytics for intelligent data collection and dissemination. These unresolved issues have been major research hotspots for many researchers since they are critical to ensuring rigid and efficient applications for intelligent data sensing, collection and dissemination in mobile computing.

To tackle the above issues and challenges, this Special Section in IEEE Access will present innovative solutions and recent advances in the domain of intelligent data sensing, collection and dissemination in mobile computing, which will provide a guide for the application and future research of mobile computing.

The topics of interest include, but are not limited to:

  • Science and foundations for computing-based intelligent sensing and data collection/dissemination, including theoretical, computational models, and new standards
  • Application of intelligent data sensing, collection and dissemination based mobile computing Infrastructures, platforms and system architectures to support mobile computing-based sensing and data collection/dissemination
  • Algorithms, schemes and techniques in mobile computing-based intelligent data sensing, data collection/dissemination to provide high performance
  • Infrastructures to support dependable, secure and safe mobile computing-based intelligent sensing and data collection/dissemination
  • Simulating and emulating environments as well as experimental results on mobile edge computing- based intelligent sensing and data collection/dissemination
  • Complexity for mobile computing of intelligent sensing and data collection/dissemination
  • Mobile-computing-based intelligent sensing and data collection/dissemination in the cloud
  • Large-scale data analysis in mobile computing-based intelligent sensing and data collection/ dissemination
  • Scalable data and resource management
  • Knowledge and service discovery in mobile computing-based sensing and data collection/ dissemination with intelligence
  • Business and societal applications of intelligent sensing and data collection/dissemination in mobile computing
  • Challenges and issues of intelligent sensing and data collection/dissemination in mobile computing
  • Other techniques in mobile computing-based intelligent sensing and data collection/dissemination, e.g., intelligent crowd sensing, social networking, and vehicular communications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Xuxun Liu, South China University of Technology, China

Guest Editors:

  1. Anfeng Liu, Central South University, China
  2. John Tadrous, Gonzaga University, USA
  3. Ligang He, University of Warwick, UK
  4. Bo Ji, Temple University, USA
  5. Zhongming Zheng, Ericsson Canada Inc, Canada

 

Relevant IEEE Access Special Sections:

  1. Mobile Edge Computing
  2. Recent Advances in Computational Intelligence Paradigms for Security and Privacy for Fog and Mobile Edge Computing
  3. Trusted Computing


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: liuxuxun@scut.edu.cn.

Artificial Intelligence Technologies for Electric Power Systems

Submission Deadline: 31 December 2019

IEEE Access invites manuscript submissions in the area of Artificial Intelligence Technologies for Electric Power Systems.

As the main energy supply system and the most complicated artificial system, the electric power system is undergoing revolutionary changes, including high-penetration renewable energy resources, complicated networks with tremendous data communications, and numerous power devices with the feature of bi-directional energy flow. Developing an intelligent power and energy system is becoming more and more urgent to promote the power production and consumption revolution and construct a clean, low-carbon, safe, and efficient energy system. Currently, artificial intelligence, as a newly developed scientific technology used to imitate, stretch, and extend the theory, method, technology, and application of human intelligence, is providing a great support for promoting the intelligence revolution of power and energy system. Artificial intelligence technology with attractive features such as deep learning, cross-border integration, man-machine cooperation, open group intelligence, and autonomous control shows the strong handling capacity in perceptual intelligence, computational intelligence, and cognitive intelligence, which shows great potential in reshaping the way of producing and utilizing the electrical energy. In particular, the combination of artificial intelligence with cloud computing, big data, internet of things (IoT), and mobile interconnection can endow the power system with features of intelligent interaction, safety, and controllability. Thus, the security, reliability, and flexibility of the power grid can be significantly improved. The revolution of the power and energy system can be highly sped up.

The goal of this Special Section in IEEE Access is to welcome the latest research in the area of Artificial Intelligence Technologies for Electric Power Systems. Reviews, surveys and traditional research articles are welcome to submit to this Special Section.

The topics of interest include, but are not limited to:

  • Image recognition technology and its application in power system security management
  • Intelligent optimization and its application in power system planning, market trade, and dispatch
  • Intelligent electric power equipment
  • Big-data-based intelligent prediction and assistant decision-making
  • Intelligence integration of renewable energy resources
  • Artificial-intelligence-based power management and consumption
  • Application of artificial intelligence in power system security and stability
  • Artificial-intelligence-based power equipment maintenance plan

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Canbing Li, Hunan University, China

Guest Editors:

  1. Hui Liu, Guangxi University, China
  2. Long Zhou, Guangdong Power Grid Co., Ltd, China
  3. Sheng Huang, Technical University of Denmark, Denmark
  4. Mingjian Cui, Southern Methodist University, USA
  5. Wuhui Chen, Jiangsu University, China
  6. Cong Zhang, Hunan University, China
  7. Jin Ma, The University of Sydney, Australia

 

Relevant IEEE Access Special Sections:

  1. Software Defined Networks for Energy Internet and Smart Grid Communications
  2. Artificial Intelligence and Cognitive Computing for Communications and Networks
  3. AI-Driven Big Data Processing: Theory, Methodology, and Applications


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: lcb@hnu.edu.cn.

Uncertainty Quantification in Robotic Applications

Submission Deadline: 01 May 2020

IEEE Access invites manuscript submissions in the area of Uncertainty Quantification in Robotic Applications.

Uncertainty in engineering systems comes from a variety of sources such as manufacturing imprecision, assembly errors, model variation and stochastic operating conditions. Hence the actual performance of an engineering system may deviate from the design target, resulting in a quality loss, customer dissatisfaction, or even catastrophic failures. To ensure robust and reliable system operations, it is imperative to quantify and reduce the uncertainty effects during the system design, manufacturing and field operation.

For the robotic systems, the dynamic and highly nonlinear performance is significantly affected by operating conditions, time-varying load, and other random stresses. This creates new challenges in measuring and characterizing the performance uncertainty with dynamic performance. Uncertainty quantification methods, such as reliability modeling, reliability analysis, reliability-based design optimization, model validation, sensitivity analysis, and robust design are deemed essential in improving the reliability of robotic systems.

This Special Section in IEEE Access invites academic scholars and industry practitioners to submit full-length articles that report the recent advances in theoretical, numerical, and experimental development in uncertainty quantification. The articles are expected to describe original findings or innovative concepts that address different aspects of uncertainty quantification challenges arising for robotic systems. New uncertainty quantification methods are anticipated to address the safety, reliability and quality issues of emerging robotic technologies, and thus move the robotic industry forward.

The topics of interest include, but are not limited to:

  • Reliability modeling, analysis and design optimization of robotic systems
  • Model verification and validation of robotic systems
  • Sensitivity analysis of robotic systems
  • Robust design of robotic systems
  • Performance reconstruction under uncertainty of robotic systems
  • Big data and machine learning in robotic systems
  • Internet of Things for robotic systems under uncertainty

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Zhonglai Wang, University of Electronic Science and Technology of China, China

Guest Editors:

  1. Tongdan Jin, Texas State University, USA
  2. Om Prakash Yadav, North Dakota State University, USA
  3. Ningcong Xiao, University of Electronic Science and Technology of China, China
  4. Yi (Leo) Chen, Glasgow Caledonian University, UK

 

Relevant IEEE Access Special Sections:

  1. Advances in Prognostics and System Health Management
  2. Additive Manufacturing Security
  3. Artificial Intelligence in Cyber Security


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: wzhonglai@uestc.edu.cn.

Security and Privacy in Emerging Decentralized Communication Environments

Submission Deadline: 30 September 2019

IEEE Access invites manuscript submissions in the area of Security and Privacy in Emerging Decentralized Communication Environments.

Modern, decentralized digital communication environments are changing with the availability of new technologies, and the development of new, real-world applications, which lead to novel challenges in security, such as: 5G/6G mobile applications, smart Internet of Things (IoT) devices, big data applications, and cloud systems. Mobile – cloud architecture is emerging as 5G /6G mobile IoT devices are generating large volumes of data, which need cloud infrastructure to process. Many IoT systems and cloud systems are decentralized and Blockchain is emerging in decentralized networks. The increasing interdependence of IT solutions accepted by society has led to a sharp increase in data. As a result, chances of data leakage or privacy infringement also increase, along with the need for new solutions for digital security and privacy protection.

This Special Section in IEEE Access aims to report highlighted security and privacy research in modern, decentralized digital communication environments. The Special Section invites experts and scholars in the fields of digital security, so that readers can keep abreast of the latest developments in the industry, and master the latest security technologies. The Special Section will support industry researchers working with emerging decentralized communication environments to solve real-world security problems. This Special Section will focus on relevant emerging digital security and privacy protection solutions.

The topics of interest include, but are not limited to:

  • Security and privacy in 5G /6G mobile / wireless networks
  • Security and privacy in the smart mobile Internet of Things
  • Security and privacy in Blockchain based decentralized networks
  • Security and privacy in 5G vehicular network
  • Security and privacy in 5G device to device communications
  • Security and privacy for big data in cloud applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:   Xiaochun Cheng, Middlesex University, UK

Guest Editors:

  1.   Zheli Liu, Nankai University, China
  2.   James Xiaojiang Du, Temple University, USA
  3.   Shui Yu,   University of Technology Sydney, Australia
  4.  Leonardo Mostarda, Università di Camerino, Italy

 

Relevant IEEE Access Special Sections:

  1. Advances in Prognostics and System Health Management
  2. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things
  3. D2D Communications: Security Issues and Resource Allocation


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: X.Cheng@mdx.ac.uk.

Distributed Computing Infrastructure for Cyber-Physical Systems

Submission Deadline: 01 November 2019

IEEE Access invites manuscript submissions in the area of Distributed Computing Infrastructure for Cyber-Physical Systems.

Advances in information communication technologies have given rise to the Internet of Things (IoT). IoT provides network infrastructures for a number of Cyber-Physical Systems (CPS), and will play an important role in our daily lives. In CPS, the massive number of deployed IoT devices (sensors, actuators, etc.) will be connected to collect data related to energy, transportation, city infrastructure, manufacturing, healthcare, and public safety, among others, supporting numerous smart-world CPS critical infrastructures such as the smart grid, smart transportation, smart health, smart city, and smart manufacturing, to name a few. As IoT devices have only limited computation and storage capacity, this calls for the development of appropriate computing infrastructures that can enable big data computing, intelligence, and storage services to support IoT-based CPS applications.

Generally speaking, more than just the integration of computing and communication with physical systems, CPS can be considered as the vertical integration of command and control, communication infrastructure, and sensing and actuation to realize complex distributed situation awareness, analysis, and decision-making. Deployed to enhance the performance of traditional systems as well as implement novel applications, CPS is characterized by critical service requirements to deliver real-time, low-latency analysis and actuation from the assessment of massive heterogeneous data. Moreover, the geo-distributed nature of sensing and actuation systems requires computing solutions that can meet the critical service needs in a likewise distributed fashion. Because of the diversity of implementations and devices, CPS infrastructures must contend with significant challenges, including the management of massively distributed heterogeneous smart devices, the synchronization of computing and storage across distributed nodes, the interaction and implementation of diverse computing paradigms (e.g., cloud, fog, edge), security and privacy concerns, problems in adaptability and scalability, and the integration of other emerging technologies (5G, machine learning, software defined networking, and network function virtualization), among others. The development of distributed computing infrastructures for CPS thus creates opportunities for novel research and necessitates interdisciplinary efforts to solve these challenges.

The articles in this Special Section in IEEE Access should focus on state-of-the-art research and challenges in the foundations and applications of distributed computing architectures and infrastructures in various CPS domains, including energy, transportation, city infrastructure, manufacturing, healthcare, and public safety.

The topics of interest include, but are not limited to:

  • Integrated Communication and Distributed Computing Design for CPS
  • Theoretical Computing Foundation and Models for CPS
  • Intelligent Real Time Data Analytics for CPS
  • Security and Privacy Issues in the Distributed Computing Infrastructure of CPS
  • Machine Learning for CPS
  • Communication and Network Architectures and Protocols for Facilitating Distributed Computing Infrastructure Deployment in CPS
  • Data Management, Trading, and Sharing in CPS
  • Integrated Testbed and Case Studies for Computing Infrastructure in CPS
  • Co-Design of Distributed Computing and Physical Systems in CPS

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:   Wei Yu, Towson University, USA

Guest Editors:

  1. Xinwen Fu, University of Central Florida, USA
  2. Jinsong Wu, University of Chile, Chile
  3. Xinyu Yang, Xi’an Jiaotong University, China
  4. Zhen Ling, Southeast University, China
  5. Zheng Chen, University of Houston, USA

 

Relevant IEEE Access Special Sections:

  1. Security and Trusted Computing for Industrial Internet of Things
  2. Towards Service-Centric Internet of Things (IoT): From Modeling to Practice
  3. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: wyu@towson.edu.

Artificial Intelligence in CyberSecurity

Submission Deadline: 30 July 2019

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in CyberSecurity.

Recent studies show that Artificial Intelligence (AI) has resulted in advances in many scientific and technological fields, i.e., AI-based medicine, AI-based transportation, and AI-based finance. It can be imagined that the era of AI will be coming to us soon. The Internet has become the largest man-made system in human history, which has a great impact on people’s daily life and work. Security is one of the most significant concerns in the development of a sustainable, resilient and prosperous Internet ecosystem. Cyber security faces many challenging issues, such as intrusion detection, privacy protection, proactive defense, anomalous behaviors, advanced threat detection and so on. What’s more, many threat variations emerge and spread continuously. Therefore, AI-assisted, self-adaptable approaches are expected to deal with these security issues. Joint consideration of the interweaving nature between AI and cyber security is a key factor for driving future secure Internet.

The use of AI in cybersecurity creates new frontiers for security research. Specifically, the AI analytic tools, i.e., reinforcement learning, big data, machine learning and game theory, make learning increasingly important for real-time analysis and decision making for quick reactions to security attacks. On the other hand, AI technology itself also brings some security issues that need to be solved. For example, data mining and machine learning create a wealth of privacy issues due to the abundance and accessibility of data. AI-based cyber security has a great impact on different industrial applications if applied in appropriate ways, such as self-driving security, secure vehicular networks, industrial control security, smart grid security, etc. This Special Section in IEEE Access will focus on AI technologies in cybersecurity and related issues. We also welcome research on AI-related theory analysis for security and privacy.

The topics of interest include, but are not limited to:

  • Reinforcement learning for cybersecurity
  • Machine learning for proactive defense
  • Big data analytics for security
  • Big data anonymization
  • Big data-based hacking incident forecasting
  • Big data analytics for secure network management
  • AI-based intrusion detection and prevention
  • AI approaches to trust and reputation
  • AI-based anomalous behavior detection
  • AI-based privacy protection
  • AI for self-driving security
  • AI for IoT security
  • AI for industrial control security
  • AI for smart grid security
  • AI for security in innovative networking
  • AI security applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:   Chi-Yuan Chen, National Ilan University, Taiwan

Guest Editors:

  1. Wei Quan, Beijing Jiaotong University, China
  2. Nan Cheng, University of Toronto, Canada
  3. Shui Yu, Deakin University, Australia
  4. Jong-Hyouk Lee, Sangmyung University, Republic of Korea
  5. Gregorio Martinez Perez, University of Murcia (UMU), Spain
  6. Hongke Zhang, Beijing Jiaotong University, China
  7. Shiuhpyng Shieh, National Chiao Tung University, Taiwan

 

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence and Cognitive Computing for Communications and Networks
  2. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things
  3. Cyber-Physical Systems


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: chiyuan.chen@ieee.org.