Blockchain Technology: Principles and Applications

Submission Deadline: 31 January 2021

IEEE Access invites manuscript submissions in the area of Blockchain Technology: Principles and Applications.

Blockchain is a disruptive technology for building consensus and trust in a peer-to-peer network without centralized control. It was first used in bitcoin, the very first cryptocurrency released at the beginning of 2009, to implement a secure ledger of transactions. This secure ledger ensures that once a transaction is placed in the ledger, it cannot be altered without being detected, which is a prerequisite for any digital currency implementation because it must guarantee that no one can double-spend one’s money. After a quiet period, the interest on blockchain has exploded in recent years. The number publications indexed by Web of Science on blockchain increased from 2 in 2013 (the first year in which publications on blockchain started to appear), to 4 in 2014, 21 in 2015, 118 in 2016, 521 in 2017, and 1,080 in 2018.

The research and developmental activities related to blockchain technology can be roughly divided into two areas: (1) The application of the blockchain in various industry sectors, such as fintech, medicine and health, energy and power generation systems, real estate, travel, manufacturing, education, or even government; (2) Fundamental research on blockchain technology itself, such as alternative consensus algorithms that consume less energy, provide better scalability, are more robust to cyberattacks, and are more scalable. In the former area, interesting issues could arise due to the particular needs of an application. For example, blockchain could be used to secure the data produced from a sensor network. However, the amount of data could easily exceed the capacity of any current blockchain platform. For the latter area, we have seen alternative consensus algorithms being proposed, such as proof of stake, that are likely to make blockchains more scalable, secure, and robust in the long term.

This Special Section welcomes original research and review articles on all aspects of blockchain technology.

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

  • Consensus algorithms
  • Cyberattacks on blockchains
  • Economic impact on cyberattacks
  • Security and trust on permissioned blockchains
  • Scalability of blockchains
  • Reliability analysis on blockchain-based systems
  • Smart contracts
  • Visualization of blockchain data
  • Blockchain for Banking and Finance
  • Blockchain for Supply Chain
  • Blockchain for Consumer Products and Retail
  • Blockchain for Government
  • Blockchain for Automotive
  • Blockchain for Medicine and Health Care
  • Blockchain for Travel and Transportation
  • Blockchain for Internet of Things
  • Blockchain for Agriculture

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

 

Associate Editor: Wenbing Zhao, Cleveland State University, USA

Guest Editors:

    1. Chunming Rong, University of Stavanger, Norway
    2. Jun Wu, Shanghai Jiao Tong University, China
    3. Zhixin Sun, Nanjing University of Posts and Telecommunications, China
    4. Srinivas Sampalli, Dalhousie University, Canada

 

Relevant IEEE Access Special Sections:

  1. Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
  2. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing
  3. New Technologies for Smart Farming 4.0: Research Challenges and Opportunities


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: w.zhao1@csuohio.edu.

Internet-of-Things Attacks and Defenses: Recent Advances and Challenges

Submission Deadline: 30 September 2020

IEEE Access invites manuscript submissions in the area of Internet-of-Things Attacks and Defenses: Recent Advances and Challenges.

The Internet of Things (IoT) technology has been widely adopted by the vast majority of businesses and is influencing every aspect of the world. However, the nature of the Internet, communication, embedded OS and backend recourses make IoT objects vulnerable to cyber attacks. In addition, most standard security solutions designed for enterprise systems are not applicable to IoT devices. As a result, we are facing a big IoT security and protection challenge, and it is urgent to analyze IoT-specific cyber attacks, and design novel and efficient security mechanisms.

The objective of the Special Section is to compile recent developments and efforts dedicated to research IoT attacks and defenses. The main purpose of this Special Section is to provide both academic and industry researchers with a forum to discuss either practical or theoretical solutions to identify IoT vulnerabilities and relevant security mechanisms. For this purpose, we encourage original research articles related to this topic, as well as high-quality review articles describing the current state of the art.

This Special Section will mainly focus on IoT-related attacks and defenses across IoT networks and devices.

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

  • Malware and unwanted software for IoT
  • Vulnerability analysis and reverse engineering for IoT
  • IoT security and privacy
  • IoT forensic techniques
  • Usable security and privacy for IoT
  • Intrusion detection and prevention for IoT
  • Cyber intelligence techniques for IoT
  • IoT infrastructures and mitigation techniques
  • IoT Hardware security
  • Cyber physical systems security
  • Adversarial learning for IoT
  • IoT Cyber crime
  • Denial-of-Service attacks for IoT
  • Security measurement for IoT
  • IoT security visualization techniques
  • Edge/Fog computing attack and defense
  • Trust models and management
  • Phishing and spam prevention

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

 

Associate Editor:  Weizhi Meng, Technical University of Denmark, Denmark

Guest Editors:

    1. Javier Lopez, University of Malaga, Spain
    2. Shouhuai Xu, University of Texas at San Antonio, USA
    3. Chunhua Su, University of Aizu, Japan
    4. Rongxing Lu, University of New Brunswick, Canada

 

Relevant IEEE Access Special Sections:

  1. Security and Trusted Computing for Industrial Internet of Things
  2. Internet-of-Things (IoT) Big Data Trust Management
  3. Security and Privacy in Applications and Services for Future Internet of Things


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: weme@dtu.dk.

Intelligent Biometric Systems for Secure Societies

Submission Deadline: 30 September 2020

IEEE Access invites manuscript submissions in the area of Intelligent Biometric Systems for Secure Societies.

Recent discourse in security domains points to the emergence of intelligent biometric systems as some of the most potent authentication systems for government agencies, border surveillance, anomaly detection, and medical data protection. New and emerging biometric research spurred scientific debate and empowered innovations in on-line security, e-banking, healthcare, and collaborative spaces, to name a few.  This Special Section on Intelligent Biometric Systems for Secure Societies in  IEEE  Access  will  focus  on  novel  biometrics  knowledge  representation  theories, methodologies, applications and technological implementations, aimed towards ensuring smarter, safer and more secure societies. Particular emphasis will be put on real-world and industrial applications supported by experimental or empirical studies.

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

  • Intelligent biometric-based authentication protocols
  • Intelligent biometric system architectures
  • Biometric-based identity and trust management
  • Cloud-based biometric identification
  • Cognitive biometric systems
  • Biometric intelligence from social media
  • Social behavioral biometrics
  • Machine learning and deep learning for biometrics
  • Multi-modal biometrics
  • Information fusion for reliable decision-making
  • Biometric-based digital rights management
  • Quality of biometric data
  • Security of biometric databases
  • Biometrics and online security
  • Biometric template protection and privacy
  • Mobile biometrics
  • Biometrics-based healthcare
  • Emerging biometrics

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

 

Associate Editor:  Marina L. Gavrilova, University of Calgary, Canada

Guest Editors:

    1. Gee-Sern Jison Hsu, National Taiwan University of Science and Technology, Taiwan
    2. Khalid Saeed, Bialystok University of Technology, Poland
    3. Svetlana Yanushkevich, University of Calgary, Canada

 

Relevant IEEE Access Special Sections:

  1. Advanced Data Mining Methods for Social Computing
  2. Distributed Computing Infrastructure for Cyber-Physical Systems
  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: mgavrilo@ucalgary.ca.

New Advances in Blockchain-Based Wireless Networks

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of New Advances in Blockchain-Based Wireless Networks.

Blockchain, as a game changer for ultra-secured and efficient digital society, has been gaining ever-increasing attention far beyond its initial application in digital currencies. One of the most fascinating topics currently is how to characterize the privacy and security in blockchain-based wireless networks. On the one hand, modern wireless communication systems are suffering from a wide range of security threats. On the other hand, traditional security operations such as encryption and protocol design are becoming increasingly incompetent for guaranteed reliability and safety in contemporary wireless networks. Against this background, providing effective blockchain proposals for efficient and secure transactions in modern wireless networks emerges as a pressing research issue both in academia and industry.

Although there have been some legacy algorithms and techniques which can prevent the disclosure of private information as well as the destruction of wireless links, such as AES encryption and beamforming in 5G networks, they may not be effective in a wide range of applications which are important to people in different specialty areas. As a matter of fact, venerability scanning has revealed a series of weaknesses in different layers of existing wireless networks. This motivates researchers in wireless security related areas to develop effective solutions to prevent the wireless systems from being hacked and/or damaged. From this point of view, our proposed Special Section will provide a valuable and timely platform for the exchange of the latest advances in this area.

A tremendous effort has been devoted to protecting privacy and security in wireless networks. Apart from many cryptography and security protocols, there has been solid work on enforcing industry standards such as the 3rd Generation Partnership Project (3GPP) and government policies (e.g., the IMT-2020 and 802.11) to grant individuals control over their own security operations. These techniques and policies aim to block the illegal disclosure of secured communication to a certain extent but may be incompetent for secured wireless transmissions at all times.

This Special Section solicits high-quality contributions that focus on the design and development of novel algorithms, technologies, and tools to address the security and privacy issues towards blockchain-based wireless networks.

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

  • New network architectures for blockchain systems
  • Performance evaluation in blockchain-based wireless networks
  • Network management in blockchain-based wireless networks
  • Privacy-aware secured protocols for blockchain-based wireless networks
  • Privacy and security in physical, link and network layer transmission for blockchain-based wireless networks
  • Heterogeneous cooperation techniques for blockchain-based wireless networks
  • Resource allocation and scheduling in blockchain-based wireless networks
  • Physical layer security in blockchain-based wireless networks
  • Cognitive and sensing techniques for blockchain-based wireless networks
  • Artificial intelligence assisted techniques for blockchain-based wireless networks
  • Routing techniques for blockchain-based wireless networks
  • Hybrid encryption techniques for blockchain-based wireless networks
  • Cross layer operations in blockchain-based wireless networks
  • Information theory and related signal processing techniques for blockchain theories, models and applications
  • Smart contracts in wireless networks
  • Semantic blockchain & knowledge-based blockchain in digital world

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

Associate Editor:  Yuan Gao, Tsinghua University, China

Guest Editors:

    1. Zhipeng Cai, Georgia State University, USA
    2. Yunchuan Sun, Beijing Normal University, China
    3. Ruidong Zhang, University of Wisconsin – Eau Claire, China
    4. Lei Zhang, University of Glasgow, UK
    5. Muhammad Zeeshan Shakir, University of the West of Scotland, UK
    6. Hamed Ahmadi, University of York, UK

 

Relevant IEEE Access Special Sections:

 

  1. Blockchain-Enabled Trustworthy Systems
  2. Secure Communication for the Next Generation 5G and IoT 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: yuangao08@tsinghua.edu.cn.

Human-driven Edge Computing (HEC)

Submission Deadline: 01 September 2020

IEEE Access invites manuscript submissions in the area of Human-driven Edge Computing (HEC).

The advent of Fifth Generation (5G) and Internet of Things (IoT) is expected to  make it possible to collect and disseminate information for various crowd-sensing services in densely populated environments. It will also result in greater demand for these services, with the rapid evolution of artificial intelligence and edge computing, which provides cloud computing and cache capabilities to reduce the computational load of cellular networks, the edges of such networks. However, the costs for deployment and maintenance of Mobile Edge Computing (MEC) are still high. Human-driven Edge Computing (HEC) is a novel model which integrates the elements of Humans, Devices, Internet and Information, and combines the power of MEC architecture and the large-scale sensing ability of Mobile Crowd-sensing (MCS). There is a great deal of research interest, from both academia and industry, on how to improve data spreading methods and environmental coverage in smart cities based on HEC. Although the study of human-driven edge computing for 5G and IoT is attractive, there are still many issues, such as fusion analysis, efficient resource usage, low latency communication, large-scale search, and data security and privacy. The objective of this Special Section is to present a collection of high-quality research articles to report the latest research advances addressing the related challenges and limitations in the area of human-driven edge computing.

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

  • Cognitive inspired HEC
  • New model, architecture and framework of HEC
  • Computation offloading in HEC
  • Resource allocation and management in HEC
  • Data harvesting, fusion and analytics
  • Fusion analysis and computing
  • Large-scale data search and recommendation
  • Deep learning and data mining in HEC
  • AI Hardware Accelerators in HEC
  • Emerging AI techniques and their combination with MEC
  • Energy-efficient and low-latency communication and computation
  • Novel QoS and QoE improvement techniques
  • Security and privacy challenges
  • Application and case studies of HEC for 5G and IoT
  • Novel techniques and future perspective in HEC

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

 

Associate Editor: Rongbo Zhu, South-Central University for Nationalities, China

Guest Editors:

    1. Lu Liu, University of Leicester, UK
    2. Ashiq Anjum, University of Derby, UK
    3. Maode Ma, Nanyang Technological University, Singapore
    4. Shiwen Mao, Auburn University, USA

 

Relevant IEEE Access Special Sections:

  1. Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs)
  2. Information Centric Wireless Networking with Edge Computing for 5G and IoT
  3. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing


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: rbzhu@mail.scuec.edu.cn.

Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications.

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent and overall effective.

It is generally acknowledged that the human brain is a multitude of times more efficient than the best artificial intelligence algorithms and machine learning models available today. This suggests that there is still something fundamental to learn from the way the brain processes information and new (biologically-inspired) ideas are needed to devise a more effective form of computation capable of competing with the efficiency of biological systems.

One of the hottest and most active research topics in the field of machine learning and artificial intelligence right now is deep learning. Deep learning models exhibit a certain kind of biological relevance, but differ significantly from what we see in the human brain in their structure and efficiency, and the way they process information. Deep learning models, such as convolutional neural networks, consist of several processing layers that represent data at multiple levels of abstraction. Such models are able to implicitly capture the intricate structures of large-scale data and are closer in terms of information processing mechanisms to biological systems than earlier so-called shallow machine learning models.

However, despite the recent progress in deep learning methodologies and their success in various fields, such as computer vision, speech technologies, natural language processing, medicine, and the like, it is obvious that current models are still unable to compete with biological intelligence. It is, therefore, natural to believe that the state of the art in this area can be further improved if bio-inspired concepts are integrated into deep learning models.

The purpose of the Special Section is to present and discuss novel ideas, research, applications and results related to techniques of image processing and computer vision approaches based on bio-inspired intelligence and deep learning methodologies. It aims to bring together researchers from various fields to report the latest findings and developments in bio-inspired image-based intelligence, with a focus on deep learning methodologies and applications, and to explore future research directions.

The topics of interest include, but are not limited to, image-based methodologies, applications, and techniques such as:

  • Bio-inspired deep model architectures
  • Theoretical understanding of bio-inspired deep architectures, models and loss functions
  • Novel bio-inspired training approaches for deep learning models
  • Effective and scalable bio-inspired parallel algorithms to train deep models
  • Bio-inspired deep learning techniques for modeling sequential (temporal) data
  • Biologically relevant adaptation techniques for deep models
  • End-to-end bio-inspired deep learning solutions
  • Bio-inspired model design
  • Bio-inspired visualizations and explanations of deep learning
  • Applications of bio-inspired deep approaches in various domains

Note that “bio-inspired” is a crucial keyword in the above list. Thus, the submissions are expected to include a discussion about the bio-inspired background of the presented method. The authors must explain how their method and its novelty correlate with what we find in nature and/or organisms, brain, psychology and similar.

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

 

Associate Editor:  Peter Peer, University of Ljubljana, Slovenia

Guest Editors:

    1. Carlos M. Travieso-González, University of Las Palmas de Gran Canaria, Spain
    2. Vijayan K. Asari, University of Dayton Vision Lab, USA
    3. Malay K. Dutta, Dr. A.P.J. Abdul Kalam Technical University, India

 

Relevant IEEE Access Special Sections:

  1. Deep Learning: Security and Forensics Research Advances and Challenges
  2. Scalable Deep Learning for Big Data
  3. Deep Learning Algorithms for Internet of Medical Things


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: peter.peer@fri.uni-lj.si.

Artificial Intelligence in Parallel and Distributed Computing

Submission Deadline: 15 January 2020

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in Parallel and Distributed Computing.

Traditional computation is driven by parallel accelerators or distributed computation nodes in order to improve computing performance, save energy, and decrease delays in accessing memory. Recently, artificial intelligent algorithms, frameworks, and computing models are growing to help with high computational performance.

To coordinate communication among professional researchers, engineers and students, and to attract and filter high quality academic contributions recommended from the International Symposium on Advanced Parallel Processing Technology (APPT 2019, http://tc.ccf.org.cn/tcarch/appt2019/), we have organized this Special Section in IEEE Access on “Artificial Intelligence in Parallel and Distributed Computing” (AIPDC). High quality contributions within the field but not presented at the conference are highly encouraged and also considered in this Special Section.

To tackle issues and challenges from the new era of artificial intelligence on computer systems, this Special Section will present innovative solutions and recent advances in the fields of intelligent algorithms, parallel computing methodologies, distributed computing models, new computer architectures, cloud computing, data centers, and so on. We are hoping the articles in this Special Section will guide future applications and research on computer architectures and computer systems.

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

  • Parallel Architectures and Hardware Systems
  • Parallel Software
  • Distributed and Cloud Computing
  • Parallel Algorithms and Applications
  • GPU neuromorphic computing, intelligent control and computing on FPGAs

 

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

Associate Editor:  Songwen Pei, University of Shanghai for Science and Technology, China

Guest Editors:

    1. Junjie Wu, National University of Defense Technology, China
    2. Tao Li, Nankai University, China
    3. Yong Chen, Texas Tech University, USA
    4. Stéphane Zuckerman, University of Cergy-Pontoise, France

 

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence in CyberSecurity
  2. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing
  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:  swpei@usst.edu.cn or songwenpei@gmail.com.

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.

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.

Mobile Edge Computing and Mobile Cloud Computing: Addressing Heterogeneity and Energy Issues of Compute and Network Resources

Submission Deadline: 30 July 2019

IEEE Access invites manuscript submissions in the area of Mobile Edge Computing and Mobile Cloud Computing: Addressing Heterogeneity and Energy Issues of Compute and Network Resources.

Mobile applications are advancing towards higher network and computation requirements which are similar to the requirements of server applications. Users prefer to perform their tasks on mobile devices instead of stationary desktop and server systems. Modern mobile applications are limited by the battery since high processing and data demands drain the batter quickly. Other resources are also limited in mobile devices such as Memory, CPU time, etc.). Mobile Edge Computing (MEC) is a paradigm that facilitates resource-scarce mobile devices to enhance their capabilities and execute data/computation-intensive applications while collaborating with resource-rich network servers to enable ubiquitous computing. Mobile Cloud Computing also provides more resources for applications that have low response requirements (non-interactive applications). Both mobile edge computing and mobile cloud computing are enabling paradigms for Internet of Things (IoT), smart grids, and e-health applications.

Smartphone applications rely on offloading techniques to leverage high-performance computing opportunities available on edge and cloud servers. Two main research challenges arise due to the heterogeneity of network and compute resources. Computation resources are unable to execute offloading and collaborative tasks without consideration of heterogeneity. The heterogeneity of computer resources can be in the form of architecture (ARM, Intel), processing power, and network capabilities. To address these issues, solutions based on application and system virtualization need to be proposed. In addition, the network heterogeneity results in varying radio capabilities for the end devices. Network access and collaboration algorithms need to consider this heterogeneity for optimal performance of applications executing on end devices. Moreover, energy is a persistent issue for most of the computing applications. Energy optimization techniques in mobile edge and mobile cloud computing can help mobile devices function longer without draining the users’ batteries.

 

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

  • Energy efficient edge computing
  • Heterogeneous resource management in edge networks
  • Smart caching
  • Edge content placement and delivery
  • D2D communication for content delivery
  • Edge content popularity prediction
  • Multi-platform computation frameworks
  • Collaborative caching

 

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 Khurram Khan, King Saud University, Saudi Arabia

Guest Editors:

  1. Junaid Shuja, Comsats University Islamabad, Pakistan
  2. Yaser Jararweh, Jordan University of Science and Technology, Jordan
  3. Guanding Yu, Zhejiang University, China
  4. Mohsen Guizani, University of Idaho, USA
  5. Christos Verikoukis, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain
  6. Raja Wasim Ahmad, Comsats University Islamabad, Pakistan

 

Relevant IEEE Access Special Sections:

  1. Towards Service-Centric Internet of Things (IoT): From Modeling to Practice
  2. Collaboration for Internet of Things
  3. Mobile Edge Computing


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: mkhurram@KSU.EDU.SA.