Collaborative Intelligence for Internet of Vehicles

Submission Deadline:  01 September 2021

IEEE Access invites manuscript submissions in the area of Collaborative Intelligence for Internet of Vehicles.   

Internet of vehicles (IoV) technology is one of the most important breakthroughs that can significantly support mobility systems toward achieving smart and sustainable societies. For example, cooperative driving features enabled by IoV can significantly decrease the risk of traffic accidents and reduce CO2 emissions, thus facilitating smarter transportation. Aerial vehicles, also known as drones, are useful for many applications, including environment and traffic monitoring, crowd mobility and gathering surveillance in pandemics, disaster recovery, and so on. Internet of underwater vehicles could enable many innovative maritime applications such as autonomous shipping, target detection, navigation, localization, and environmental pollution control. However, the development of IoV systems is dependent on overcoming the following two main challenges.

First, due to the heterogeneity of networking entities, strict application and data processing requirements, and limited resources in IoV environments, more advanced networking and computing technologies are required. Future IoV systems feature a larger number of devices and multi-access environments where different types of wireless spectrums should be efficiently utilized. At the same time, novel services, such as cooperative autonomous driving, IoV-based safety and traffic efficiency applications are emerging, and demand unprecedented high accuracy and reliability, ultra-low latency, and large bandwidth. This poses crucial challenges to the efficient use of the limited networking and computing resources.

Recently, to further explore the value of big data from IoV systems, artificial intelligence (AI)-based approaches have been attracting great interest in empowering computer systems. Some collaborative learning approaches, such as federated learning and multi-agent systems, have been used to reduce network traffic and improve the learning efficiency of some smartphone applications. For IoV systems, collaborative intelligence can be achieved via an efficient collaboration among heterogeneous entities, including vehicles, edge servers, and the cloud.

Second, in order to enable a smarter society, more research should be conducted on developing collaborative IoV frameworks and systems to expedite the applications of emerging IoV technologies. An efficient use of cross-domain big data should be discussed, and academic-industrial collaborations should be promoted to solve the existing problems toward a smarter society.

This Special Section focuses on the technical challenges for enabling collaborative IoV systems, and the applications of IoV technologies for a smarter society.

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

  • Collaboration among Space, Air, Ground, and Sea mobile networks
  • Collaborative intelligence based on cross-domain big data for IoV
  • Collaborative networking for IoV
  • Collaborative computing for IoV
  • Collaborative IoV for smart cities
  • Collaborative IoV for intelligent transportation systems
  • Collaborative IoV for energy-efficient sustainable cities
  • Collaborative electric vehicles
  • Collaborative unmanned aerial vehicles
  • Collaborative heterogeneous unmanned ground and aerial vehicles
  • Collaborative underwater vehicle technologies for smart ocean
  • Collaborative IoV for smarter society
  • Collaborative learning for IoV
  • Data driven collaborative intelligence for IoV
  • End-edge-cloud collaboration for IoV
  • New networking and computing architectures for Collaborative IoV
  • Security & privacy for IoV

 

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

 

Associate Editor:  Celimuge Wu, The University of Electro-Communications, Japan

Guest Editors:

    1. Soufiene Djahel, Manchester Metropolitan University, UK
    2. Damla Turgut, University of Central Florida, USA
    3. Sidi-Mohammed Senouci, University of Bourgogne, France
    4. Lei Zhong, Toyota Motor Corporation, Japan

 

Relevant IEEE Access Special Sections:

    1. Artificial Intelligence (AI)-Empowered Intelligent Transportation SystemsBeyond 5G Communications
    2. Edge Intelligence for Internet of ThingsMillimeter-Wave Communications: New Research Trends and Challenges
    3. Information Centric Wireless Networking with Edge Computing for 5G and IoT

 

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: celimuge@uec.ac.jp.

Lightweight Security and Provenance for Internet of Health Things

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Lightweight Security and Provenance for Internet of Health Things.

As an extension of the Internet of Things (IoT), the Internet of Health Things (IoHT), play an important role in the remote exchange of data of different physical processes such as patient monitoring, treatment progress, observation and consultation. In IoHT, the connectivity, integration, computation and interoperability are enabled through various sensors, actuators, and controllers, thereby providing seamless connectivity with efficient utilization of resources. In emergency situations, when a patient is being shifted to a hospital, seamless connectivity between Ambulance to Hospital (A2H), Hospital to Hospital (H2H) and Hospital to Ambulance (H2A), is very critical. With advances in tele-medicine, telesurgery, and other health-care applications, streaming has become an essential part of IoHT. The data traffic in IoHT applications, such as interactive multimedia streaming, traffic generated from faulty sensors, and vital signs, can tolerate packet loss but have stringent delay requirements. On the other hand, video streaming applications cannot tolerate jitter. Similarly, the low-power devices are sensitive to packet loss, and the periodic physiological traffic of medical traffic can tolerate delay, or jitter, but not packet loss.  Routing data in different IoHT applications has varying quality of service (QoS) requirements in terms of delay, packet loss, jitter, and throughput. Most of the algorithms used today to secure the data and cryptography techniques in IoHT contain high computational complexities with high energy consumption. However, due to the energy limitations of low-power embedded devices, traditional cryptographic solutions are not viable for most of the IoHT applications. Less computational complexity, less space acquisition and energy-efficient security primitives are key building blocks for end-to-end content protection, user authentication, and consumer confidentiality in the IoHT.  Once the data is gathered from different applications, it must be accurate and information about its origin should also be known. Due to scalability, tiny devices installed in IoHT are not usually physically protected. Data security and provenance therefore serve as the backbone for implementing IoHT applications.

This Special Section targets original technical articles with novel contributions on the improvement of security of IoHT, in particular by finding the correct lightweight solution. Review articles of high quality that provide thorough overview of the subject will also be considered. The topics of interest include, but are not limited to:

  • Lightweight security for IoHT
  • Low energy IoHT systems
  • Low energy security algorithms for A2H, H2H, and H2A in IoHT
  • Lightweight solutions for data forensics in IoHT
  • Lightweight routing algorithms for data provenance in IoHT
  • Secure lightweight protocols for A2H, H2H, and H2A in IoHT
  • Security framework and architecture for IoHT
  • Lightweight video streaming mechanism for IoHT

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

 

Associate Editor:  Muhammad Tariq, FAST National University of computer & Emerging Sciences, Pakistan and Princeton University, USA

 

Guest Editors:

    1. Takuro Sato, Waseda University, Waseda University, Tokyo, Japan
    2. Gautam Srivastava, Brandon University, Canada
    3. Vuk Marojevic, Mississippi State University, USA
    4. Mario Goldenbaum, Bremen University, Bremen, Germany

 

Relevant IEEE Access Special Sections:

  1. Secure Communication for the Next Generation 5G and IoT Networks
  2. Deep Learning: Security and Forensics Research Advances and Challenges
  3. Emerging Approaches to Cyber Security


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: mtariq@princeton.edu.

Intelligent Logistics Based on Big Data

Submission Deadline: 20 May 2020

IEEE Access invites manuscript submissions in the area of Intelligent Logistics Based on Big Data.

The advent of the era of big data and the rapid development of e-commerce have provided a new development direction for the modern logistics industry, prompting the logistics industry to think more about data. In addition, the operation mode has gradually changed from the traditional extensive mode to the intelligent logistics one, characterized by information, data, sharing and intelligence.

Intelligent logistics based on big data has significantly improved the intelligence level of warehousing, transportation and distribution, including the intelligent location of logistics outlets, the optimal configuration of transportation routes, the highest loading rate of transportation vehicles, and the optimal distribution of the last mile, which can be used to explore greater potential business value through massive logistics data analysis.

The goal of this Special Section in IEEE Access is to provide a specific opportunity to review the state-of-the-art of intelligent logistics in big data, and bring together researchers in the relevant areas to share the latest progress, novel methodologies and potential research topics.

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

  • Design and development of intelligent logistics system
  • Data collection and knowledge management for intelligent logistics based on Big Data
  • Analysis of intelligent logistics mode based on Big Data
  • Development of smart logistics systems using Big Data
  • Emergency logistics modeling and optimization based on Big Data
  • Optimal design of manufacturing/remanufacturing logistics network
  • Data-driven-based intelligent logistics management methods & technologies
  • Internet-of-things-based intelligent logistics design and optimization
  • Environment analysis of reverse logistics based on Big Data
  • Modeling of network design for intelligent logistics using Big Data

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

 

Associate Editor:  Zhiwu Li, Macau University of Science and Technology, Macau

Guest Editors:

    1. Guangdong Tian, Shandong University, China
    2. Di Wu, Hunan University, China
    3. MengChu Zhou, New Jersey Institute of Technology, Newark, USA
    4. Feng Chu, Univeristy of Paris-Saclay and University of Evry, France

 

Relevant IEEE Access Special Sections:

  1. Applications of Big Data in Social Sciences
  2. AI-Driven Big Data Processing: Theory, Methodology, and Applications
  3. Urban Computing and Intelligence


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: systemscontrol@gmail.com.

Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems

Submission Deadline: 01 June 2020

IEEE Access invites manuscript submissions in the area of Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems.

The topic of Artificial Intelligence (AI)- Empowered Intelligent Transportation Systems (ITS) has drawn more attention recently, with the rapid development of ubiquitous networks and smart vehicles. Researchers around the world have been working on new automotive applications to create a comfortable and safer driving environment. Current challenges include: how to run computing-intensive applications on vehicles; how to enable real-time feedback between vehicles and the traffic management server based on the current Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication modes; and how to provide efficient computing capabilities for resource-consumption applications, and reasonable resource allocation for vehicles and infrastructures. AI-Empowered solutions, such as deep learning and reinforcement learning, should help relieve computational loads for vehicles. Recently, AI has achieved remarkable achievements in many fields, such as image processing, pattern recognition, and natural language processing, etc. It is also involved in computing-intensive applications, such as autopilot and real-time navigation through V2V or V2I. However, AI-Empowered ITS is still in its infancy. How can AI be integrated with ITS and make it work well in dynamic vehicular network scenarios? Furthermore, there are still questions on how to design more efficient AI solutions for resource management in ITS.

The objective of this Special Section in IEEE Access is to introduce the current developments and advancements of the technical elements of the AI-Empowered ITS, from both theoretical and practical perspectives.

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

  • Architecture and framework establishment of AI-Empowered ITS
  • Design of efficient AI solutions in ITS
  • AI-Empowered approach of route planning in ITS
  • AI-Empowered approach of traffic scheduling in ITS
  • AI-Empowered resource management in ITS
  • AI-Empowered security and privacy protection in ITS
  • AI-Empowered real-time applications in ITS
  • Testing and evaluation tools for AI-Empowered ITS
  • Novel applications based on AI-Empowered ITS
  • Future AI-Empowered ITS: challenges and open issues

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

 

Associate Editor:  Edith Ngai, Uppsala University, Sweden

Guest Editors:

    1. Chao Chen, Chongqing University, China
    2. Amr M. Tolba, King Saud University, Saudi Arabia
    3. Mohammad S. Obaidat, Fordham University, USA
    4. Fanzhao Wang, Huawei Technologies Co Ltd, China

 

Relevant IEEE Access Special Sections:

  1. Big Data Technology and Applications in Intelligent Transportation
  2. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems
  3. Communication, Control, and Computation Issues in Heterogeneous Vehicular 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:  edith.ngai@it.uu.se.

Big Data Technology and Applications in Intelligent Transportation

Submission Deadline: 31 March 2020

IEEE Access invites manuscript submissions in the area of Big Data Technology and Applications in Intelligent Transportation.

Intelligent transportation is an emerging trending topic in the frontier of world transportation development. It relies on the integration of transport infrastructure and vehicle technology, and aims at building a safe, convenient, efficient and green transportation system through the integration of modern information, communication and control. It includes four main parts: intelligent transport, intelligent vehicle, intelligent traffic management, intelligent plan and applications.

With the improvement of the Internet of Vehicles, road network monitoring, navigation systems, logistics supervision and other platforms, the sources and categories of traffic big data have increased in recent years. Massive multi-source traffic big data provides valuable data resources for intelligent traffic management. Based on big data, emerging technologies such as cloud computing and artificial intelligence make traffic more intelligent, green and safe.

This Special Section in IEEE Access aims to provide researchers and practitioners a platform to present innovative solutions based on Big Data Technology and Applications. The focus of this Special Section is to address the current research challenges by encouraging submissions related to the advanced Big Data Technology and Applications in Intelligent Transportation System.

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

  • Urban Traffic Big Data
  • Road Network Travel Big Data Analysis
  • Rail Traffic Big Data Analysis
  • Civil Aviation Big Data Application
  • Big Data and Traffic Safety
  • Big Data and Traffic Optimization
  • Big Data in Ports, Waterways, Inland Navigation, and Vessel Traffic Management
  • Big Data in Detection of Vulnerable Road Users and Animals
  • Big Data and Air, Road, and Rail Traffic Management
  • Big Data in ITS User Services
  • Big Data in Emergency Management
  • Big Data in Transportation Electrification
  • Big Data in Emissions, Noise, Environment
  • Big Data in Management of Exceptional Events
  • Big Data in Intelligent Logistics
  • Big Data in Sensing, Detectors and Actuators
  • Big Data in Intelligent Vehicles
  • Big Data in Vision, and Environment Perception
  • Smart Mobility
  • Shared Mobility
  • Big Data in Safety Systems
  • Testing for Big Data Application in ITS

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

 

Associate Editor:  Sabah Mohammed, Lakehead University, Canada

Guest Editors:

    1. Xiaobo QU, Chalmers University of Technology, Sweden
    2. Hamid Arabnia, The University of Georgia, USA
    3. Jiandong Zhao, Beijing Jiaotong University, China
    4. Dalin Zhang, Beijing Jiaotong University, China
    5. Tai-Hoon Kim, University of Tasmania, Australia, Beijing Jiaotong University, China

 

Relevant IEEE Access Special Sections:

  1. Data Mining for Internet of Things
  2. Urban Computing and Intelligence
  3. Distributed Computing Infrastructure for Cyber-Physical Systems


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: sabah.mohammed@lakeheadu.ca.

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.

5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Submission Deadline: 30 September 2019

IEEE Access invites manuscript submissions in the area of 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility.

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050 more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities and their commuter belts, reliable high-rate wireless communication will not only be required for (quasi-) static users, but also for hosts of people moving in public and private transportation networks. Yet, wireless connectivity is not restricted to people; frictionless functioning of such a society in motion is supported by Intelligent Mobility where each connected transportation vehicle (car, train, bus, ship, aircraft, motorcycle, bicycle) is expected to be a smart object equipped with a powerful multi-sensor platform, communication capability, computing units, and Internet protocol (IP)-based connectivity, such as to be highly efficient in various vehicular and transportation applications. This vision requires a more pervasive and ubiquitous communications and networking core, which will not be only driven by the existing research on 5G, but also enabled by future mobile wireless communications which employ new concepts, such as data analytics, artificial intelligence, machine learning, cloud-computing, etc. Therefore, this Special Section in IEEE Access focuses on various theoretical and experimental views on researching and developing the required technological enhancements of 5G and beyond mobile wireless communications to efficiently support the vision of intelligent mobility, providing mobility as a service and enabling dependable Internet services.

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

  • Propagation and channel measurement and modeling for connected cars, trains, ships, and aircrafts, especially at new frequency bands
  • Integrated space-air-vehicle-ground networks
  • Integration of artificial intelligence and machine learning into new wireless systems solutions and applications for intelligent mobility
  • Data analytics for intelligent transportation systems
  • Cloud- and edge based high-performance computing techniques for mobile networks
  • MIMO and Massive MIMO for intelligent transportation systems
  • Radio technologies for high mobility transportation systems
  • Physical layer techniques for connected vehicles, public transportation control and signaling
  • Wireless technologies for automated and connected vehicles
  • Millimeter wave, sub-millimeter wave, and THz communications enabling intelligent mobility
  • Heterogeneous networks and distributed antenna systems
  • Novel physical layer waveforms and modulation schemes

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

 

Associate Editor:  Ke Guan, Beijing Jiaotong University, China

Guest Editors:

  1. Markus Rupp, Vienna University of Technology, Austria
  2. Thomas Kürner, Technische Universität Braunschweig, Germany
  3. Cesar Briso, Polytechnic University of Madrid, Spain
  4. David W. Matolak, University of South Carolina, USA
  5. Jun-ichi Takada, Tokyo Institute of Technology, Japan
  6. Wei Wang, Chang’an University, China

 

Relevant IEEE Access Special Sections:

  1. Advances in Statistical Channel Modeling for Future Wireless Communications Networks
  2. Millimeter-wave and Terahertz Propagation, Channel Modeling and Applications
  3. Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward


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: kguan@bjtu.edu.cn.

Visual Analysis for CPS Data

Submission Deadline: 31 March 2020

IEEE Access invites manuscript submissions in the area of Visual Analysis for CPS Data.

Ubiquitous sensing technologies, social media and large-scale computing infrastructures have produced a variety of CPS (cyber-physical-social) data, e.g., Twitter/WeChat posts, human mobility, car trajectories, phone calls, WeChat connections, and geographical data. Analyzing CPS data can provide solutions for green, high-efficient and intelligent production and lifestyles. However, CPS data is usually massive, heterogeneous and distributed, and consequently cannot be analyzed effectively by analysts with traditional data processing techniques. The goal of Visual Analysis for CPS Data is to develop methods and tools that can help analysts understand and utilize CPS data to gain insight and make decisions in an interactive and iterative way. To facilitate management of CPS-relevant future applications, visual encodings, visual interfaces and visual interactions are essential components that integrate (or combine) human intelligence with machine intelligence.

The Special Section in IEEE Access on “Visual Analysis for CPS Data” of IEEE Access aims to address issues related to the representation, visual design, visual mapping, interaction, analysis and applications of multi-variate and time-varying data collected in a CPS system (e.g., smart city, MOOCs, smart factory, ITS). We solicit articles describing frameworks, theories, approaches, and techniques from visualization, visual data mining and visual analysis for designing, building and managing CPS systems.

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

  • Visual representation, visual design, visual interaction, visual reasoning, visual decision-making for CPS data
  • Visualization theories and visual analysis models for CPS systems and applications
  • Novel visual data mining, visual machine learning pipelines for CPS data, and applications, surveys, and evaluation approaches of visual-assisted CPS systems
  • Visualization and visual analysis theories for CPS data analysis
  • Visual representations and interaction techniques for CPS data analysis
  • Novel visual data mining and visual machine learning pipelines for CPS data analysis
  • Visual-assisted CPS data management and knowledge representation
  • Visual-supported modeling, planning and decision-making for CPS systems and applications
  • Collections, benchmarking and evaluations for visual analysis of CPS data
  • Surveys of visual-assisted CPS systems and application

 

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

 

Associate Editor:  Shuiguang Deng, Zhejiang University, China

Guest Editors:

  1. Wei Chen, Zhejiang University, China
  2. Ye Zhao, the Kent State University, USA
  3. Xinheng (Henry) Wang, University of West London, UK
  4. Panpan Xu, Bosch Research North America, USA

 

Relevant IEEE Access Special Sections:

  1. Applications of Big Data in Social Sciences
  2. Advanced Software and Data Engineering for Secure Societies
  3. AI-Driven Big Data Processing: Theory, Methodology, and Applications


IEEE Access Editor-in-Chief:  Derek Abbott, Professor, 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: dengsg@zju.edu.cn.

Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward

Submission Deadline: 01 July 2019

IEEE Access invites manuscript submissions in the area of Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward.

With the rapid development in the fields of wireless ad hoc networks that do not rely on any pre-existing infrastructure, Flying Ad hoc networks (FANETs) have recently captured the attention of vendors and investors due to the flying nature of entities in the network. FANET is composed of unmanned nodes that fly at high altitude platforms such as balloons, unmanned aerial vehicles or drones. The network of nodes that fly at high altitude has gained commercial and industrial popularity because of its applications in surveillance, agriculture, photography, etc.  New applications that are being developed for FANET bring up new challenges such as multipath propagations, severe shadowing, traffic load balancing, mobility, congestion, high error rates, etc., that usually result in performance degradation of the network. However, the applications developed and used in FANET may also result in collision with other air traffic due to the above challenges.

The Federal Aviation Administration has  reported about the tremendous increase of more than 50% in  air traffic in unmanned vehicles in 2017. However, such an increase in the UAVs results in an increase in the network traffic of FANET that may lead to an unbalanced traffic distribution, resulting in an increase in packet loss. Furthermore, the high data traffic generated by the number of nodes in FANET is one of the leading causes of accidents with the commercial flights. In order to cope with such challenges, the network traffic of FANET must be distributed in such a way that it does not disturb commercial flights or the communication among the nodes that fly at high altitudes in a network.

This Special Section in IEEE Access therefore solicits original research work, novel protocols, methodologies and survey papers addressing the future challenges and solutions that embark on network resource management in FANETs.

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

  • Efficient deployment of unmanned aerial vehicles (UAVs) at high altitude platforms (HAPs) for congestion avoidance and control
  • Dynamic traffic load balancing for congestion avoidance through routing in Flying Ad hoc Networks
  • Performance investigation of 5G systems with flying ad hoc networks (FANETs)
  • An optimal data collection and dissemination technique for balanced traffic utilization in FANETs
  • Distributed congestion-aware position oriented MAC/Routing protocols for FANETs
  • Performance evaluation of layered protocols of TCP/IP for multimedia traffic in flying ad hoc networks (FANETs) at different altitude platforms
  • Analysis of Reactive, proactive, and hybrid routing protocols for flying Ad Hoc networks
  • Opportunistic routing for distributed video traffic dissemination over flying ad hoc networks
  • A cross layer design for distributed information dissemination over flying ad hoc networks
  • Agricultural environment monitoring system based on UAV in FANETs
  • Congestion avoidance, detection, and mitigation in Flying Ad-Hoc Network for efficient utilization of network resources
  • Distributed clustering approach for FANETs
  • Enhanced connectivity for robust multimedia transmission in UAV networks
  • Active Queue Management for resource sharing in Flying Ad hoc Networks
  • Bio-inspired routing protocols for FANET routing
  • Multi-hop and relay-based communications for distributed traffic load balancing
  • Smart solutions to reduce congestion in FANETs
  • Interaction of FANET with IoT
  • Distributed Emergency Message Dissemination in FANET

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

 

Associate Editor: Omer Chughtai, COMSATS University Islamabad, Wah Campus, Pakistan

Guest Editors:

  1. Mubashir Husain Rehmani, Waterford Institute of Technology, Ireland
  2. Leila Musavian, University of Essex, UK
  3. Sidi-Mohammed Senouci, University of Bourgogne, France
  4. Soumaya Cherkaoui, Université de Sherbrooke, Canada
  5. Shiwen Mao, Auburn University, USA
  6. Onur Alparslan, Osaka University, Japan

 

Relevant IEEE Access Special Sections:

  1. Fairness in Futuristic Wireless Networks: Applications, Implementation, Issues, and Opportunities
  2. Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling
  3. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact:  umar.chughtai@gmail.com

Emerging Technologies for Vehicle to Everything (V2X)

Submission Deadline: 15 December 2018

IEEE Access invites manuscript submissions in the area of Emerging Technologies for Vehicle to Everything (V2X).

Recently, the vehicle to everything (V2X) paradigm is attracting more attention from both academia and industry. In V2X, while connecting all the devices (motor-vehicle, non-motor-vehicle, bicycle, pedestrian, etc.) on the road, we can collect and share the real-time information (speed, accelerate, route, etc.) among V2X devices for automatic piloting and intelligent traffic control. On the other hand, to accelerate the automatic piloting technologies, big data and deep learning-based image recognition and environment reconstruction is an inevitable technology. In addition to intelligent traffic and automatic driving technologies, 5G will also play a significant role in V2X by providing fast speed transmissions for in-car entertainment (4K/8K high-definition video, etc.), as well as for vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-network (V2N) communications. Meanwhile, with V2X’s massive number of connected devices, information centric networking (ICN)/content caching technologies can be exploited for optimal vehicle network routing and wireless information delivery, which will leverage the network and wireless transmission performance. Together with the adoption of optimal routing, ICN-based network architecture will further alleviate the backhaul load. In V2X, to meet the different quality of service (QoS) requirements of a massive number of connected devices, the software defined network (SDN) based network slicing technology can be invoked to create different dedicated network slices.  Based on all those discussions, it is known that to accomplish the goal of V2X, comprehensive solutions are needed to reshape existing networks. Moreover, because of the massive number of connected devices on the road, the future of driving and traffic will be reshaped, and policies on this forthcoming V2X era from the government should be set forth as well.

However, until now, only the V2X’s initial ambitions regarding intelligent traffic control, automatic driving and fast speed transmission experiences are sketched. So, comprehensive technologies and policies able to accomplish all the goals of V2X from academia, industry and government are still needed. This Special Section in IEEE Access aims to bring together researchers to report their recent research advances in V2X and exchange new ideas with innovative technologies and solutions. This Special Section will include a collection of outstanding research-oriented review and survey articles, high level position papers and new research results, covering a wide range of topics within V2X systems and networks.

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

  • DSRC technologies for V2X
  • C-V2X technologies for V2X
  • Signal processing technologies for V2X
  • Channel estimation and measurement technologies for V2X
  • Front-hauling and back-hauling technologies for V2X
  • Resource allocation and optimization for V2X
  • Energy efficiency analysis for V2X
  • Heterogeneous network technologies for V2X
  • Cyber security and application scenarios for V2X
  • Software defined network architectures for V2X
  • Network slicing technologies for V2X
  • ICN and SDN technologies-based network architectures for V2X
  • Unmanned aerial vehicle (UAV) assisted communications for V2X
  • Centralized and decentralized network architectures for V2X
  • Integrated vehicle edge, fog computing technologies for V2X
  • Data mining technologies for V2X
  • Vehicle and pedestrian behavior prediction technologies for V2X
  • Machine learning iteration algorithms for V2X
  • Deep learning-based image detection for V2X
  • Deep learning based 2-D, 3-D environment reconstructions for V2X
  • Big data and machine learning based technologies for V2X
  • Legislation, standardization and enforcement for V2X

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

 

Associate Editor: Yan Zhang, University of Oslo, Norway


Guest Editors:

  1. Di Zhang, Zhengzhou University, China
  2. Zhi Liu, Waseda University, Japan
  3. Carlos Tavares Calafate, Technical University of Valencia (UPV), Spain
  4. Yi Liu, Guangdong University of Technology (GDUT), China
  5. Anwer Al-Dulaimi, EXFO Inc., Canada

 

Relevant IEEE Access Special Sections:

  1. High Mobility 5G LTE-V: Challenges and Solutions
  2. Security and Privacy for Vehicular Networks
  3. Recent Advances on Modelling, Optimization and Signal Processing Methods in Vehicle Dynamics and Crash-worthiness


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: di_zhang@zzu.edu.cn (GE), yanzhang@ifi.uio.no (AE).