Pushing Artificial Intelligence to Edge: Emerging Trends, Issues and Challenges

  in Special Issue   Posted on June 13, 2019

Information for the Special Issue

Special Issue Call for Papers:

Aims and Scope

Driven by the Internet of Things (IoT), a new computing model – Edge computing – is currently evolving, which allows IoT data processing, storage and service supply to be moved from Cloud to the local Edge devices such as smart phones, smart gateways or routers and base stations that can offer computing and storage capabilities on a smaller scale in real-time. EoT pushes data storage, computing and controls closer to the IoT data source(s); therefore, it enables each Edge device to play its own role of determining what information should be stored or processed locally and what needs to be sent to the Cloud for further use. Thus, EoT enables IoT services to meet the requirements of low latency, high scalability and energy efficiency, as well as to mitigate the traffic burdens of the transport network.

However, current expansion of the IoT and digital transformation is generating new demands on computing and networking infrastructures across all industries (automotive, aerospace, life safety, medical, entertainment and manufacturing, etc). Hence, it is becoming challenging for Edge computing to deal with these emerging IoT environments. In order to overcome this issue, there is a need for intelligent Edge or Artificial Intelligence (AI) powered Edge computing (Edge-AI) to manage all the new data needs from these sectors. AI with its machine learning (ML) abilities can be fused into Edge to extend its power for intelligently investigating, collecting, storing and processing the large amounts of IoT data to maximize the potential of data analytics and decision-making in real time with minimum delay. There are many application areas where Edge-AI can be used, such as fall detection systems for the elderly, intelligent clothes for safety applications, smart access systems, smart camera, smart fitness systems, pet monitoring systems, self-predictive electric drives, and so on.

While researchers and practitioners have been making progress within the area of Edge-AI, still there exist several challenging issues that need to be addressed for its large-scale adoption. Some of these issues are: credibility and trust management, distributed optimization of multi-agent system in Edge, self-organization, self-configuration, and self-discovery of edge nodes, lack of standards in containerization area (Docker, Open Container Initiative etc.) for Edge-AI, security risk for the data that needs to be processed at the edge, lack of efficient scheduling algorithms to optimize AI or machine learning in Edge computing structure, new operating system for edge artificial intelligence, etc.

Topics of Interest

This special issue targets a mixed audience of researchers, academics and industries from different communities to share and exchange new ideas, approaches, theories and practice to resolve the challenging issues associated with the leveraging of intelligent Edge paradigm. Therefore, the suggested topics of interest for this special issue include, but are not limited to:

  • Novel middleware support for Edge intelligence
  • Network function virtualization technologies that leverage Edge intelligence
  • Trust, security and privacy issues for Edge-AI
  • Distributed optimization of multi agent systems for Edge intelligence
  • Self-organization, self-configuration, and self-discovery of Edge node
  • Semantic interoperability for Edge intelligence
  • Autonomic resource management for Edge-AI
  • Mobility, Interoperability and Context-awareness management for Edge-AI
  • Container based approach to implement AI in Edge
  • Applications/services for Edge artificial intelligence
  • New operating system for Edge intelligence
  • 5G-enabled services for Edge intelligence
  • Software and simulation platform for Edge AI
  • AI, Blockchain and Edge computing

Review of submissions

High quality paper selection criteria and a prompt review process will be ensured. The submission evaluation will follow the standard Engineering Applications of Artificial Intelligence (EAAI) journal review process with all standard rules applied. Once the paper submission deadline is passed, the lead Guest Editor (GE) will communicate with the other GEs regarding the number of submissions and assign the papers to them by considering their expertise. The assigned GEs will be responsible for the review process, and submit their recommendations along with the reviews to the Editor-in-Chief (EIC), and the EIC will then make the final acceptance or rejection decisions and communicate with authors. To avoid conflicts of interest, no guest editor should appear as author/co-author for any submission to the Special Issue.

Proposed Schedule

Deadline for submission: Nov 15, 2019

1st round of review – comments to authors: Jan 15, 2020

Revision deadline: Feb 28, 2020

Submission of final version: Apr 30, 2020

Guest Editors

Giancarlo Fortino, University of Calabria, Italy (g.fortino@unical.it)

Mengchu Zhou, New Jersey Institute of Technology, USA (mengchu.zhou@njit.edu)

Mohammad Mehedi Hassan, King Saud University, Riyadh Saudi Arabia (mmhassan@ksu.edu.sa)

Mukaddim Pathan, Telstra Ltd., Australia (Mukaddim.Pathan@team.telstra.com)

Stamatis Karnouskos, SAP, Germany (karnouskos@ieee.org)

Biographies of Guest Editors

Prof. Giancarlo Fortino (SM\’12) is Full Professor of Computer Engineering at the Dept. of Informatics, Modeling, Electronics, and Systems of the University of Calabria (Unical), Italy. He received a Ph.D. in Computer Engineering from Unical in 2000. He is also guest professor at Wuhan University of Technology (Wuhan, China), high-end expert at HUST (China), and senior research fellow at the Italian National Research Council ICAR Institute. He is the director of the SPEME lab at Unical as well as co-chair of Joint labs on IoT established between Unical and WUT and SMU Chinese universities, respectively. His research interests include agent-based computing, wireless (body) sensor networks, and Internet of Things. He is author of over 400 papers in int\’l journals, conferences and books. He is (founding) series editor of IEEE Press Book Series on Human-Machine Systems and EiC of Springer Internet of Things series and AE of many int\’l journals such as IEEE TAC, IEEE THMS, IEEE IoTJ, IEEE SJ, IEEE SMCM, Information Fusion, JNCA, EAAI, etc. He is cofounder and CEO of SenSysCal S.r.l., a Unical spinoff focused on innovative IoT systems. Fortino is currently member of the IEEE SMCS BoG and of the IEEE Press BoG, and chair of the IEEE SMCS Italian Chapter.

Prof. MengChu Zhou (S\’88-M\’90-SM\’93-F\’03) received his B.S. degree in Control Engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, M.S. degree in Automatic Control from Beijing Institute of Technology, Beijing, China in 1986, and Ph. D. degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, NY in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests are in Petri nets, Internet of Things, big data, web services, manufacturing, transportation, and energy systems. He has over 640 publications including 12 books, 330+ journal papers (240+ in IEEE Transactions), and 28 book-chapters. Dr. Zhou is a recipient of CIM University-LEAD Award by Society of Manufacturing Engineers, Perlis Research Award and Fenster Innovation in Engineering Education Award by NJIT, Humboldt Research Award for US Senior Scientists, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society. He has been among most highly cited scholars for years and ranked top one in the field of engineering worldwide in 2012 by Web of Science/Thomson Reuters. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of IEEE, International Federation of Automatic Control (IFAC) and American Association for the Advancement of Science (AAAS). He has actively participated in and contributed to IEEE World Forum of IoT and has been a member of IEEE IoT Initiative Committee and IEEE Smart City Initiative Committee. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering. He served/is serving as Associate Editor, Editor and Managing Editor of several IEEE Transactions. He is presently guest-editing a special issue on \”Advances and Applications of Internet of Things for Smart Automated Systems\” of IEEE Transactions on Automation Science and Engineering. He also served as Program Chair and General Chair of over a dozen international conferences.

Dr. Mohammad Mehedi Hassan (SM\’18) is currently an Associate Professor of Information Systems Department in the College of Computer and Information Sciences (CCIS), King Saud University (KSU), Riyadh, Kingdom of Saudi Arabia. He received his Ph.D. degree in Computer Engineering from Kyung Hee University, South Korea in February 2011. He has authored and coauthored around 180+ publications including refereed IEEE/ACM/Springer/Elsevier journals, conference papers, books, and book chapters. Recently, his 4 publications have been recognized as the ESI Highly Cited Papers. He has served as chair, and Technical Program Committee member in numerous reputed international conferences/workshops such as IEEE CCNC, ACM BodyNets, IEEE HPCC etc. He is a recipient of a number of awards including Best Journal Paper Award from IEEE Systems Journal in 2018, Best Paper Award from CloudComp in 2014 conference, and the Excellence in Research Award from King Saud University (2 times in row, 2015 & 2016). He is on the editorial board of IEEE Access, and Elsevier Computer and Electrical Engineering Journal. He has also played role of the guest editor of several international ISI-indexed journals such as IEEE Internet of Things, Information Sciences (Elsevier), Future Generation Computer Systems (Elsevier), Multimedia Tools and Applications (Springer), Cluster Computing (Springer), Computers and Electrical Engineering (Elsevier) and Journal of Parallel and Distributed Computing (Elsevier). He has secured several national and international research grants in the domain of cloud computing and sensor network. His research interests include Cloud computing, Edge computing, Internet of things, Body sensor network, Big data, Deep learning, Mobile cloud, Smart computing, Wireless sensor network, 5G network, and social network. He is a Senior Member of the IEEE.

Dr. Mukaddim Pathan heads up the End-to-End Architecture & Technology Practices group for Networks & IT within Telstra, the largest Telecommunications company in Australia. He is a leading personnel in the Telecommunications and Digital Media industry, with 10+ years of senior management experience. He holds a PhD in Computer Science, specialising in content delivery and video streaming, and MBA in Strategy and Operations from the University of Melbourne, Australia. His research interests include data management, resource allocation, load balancing and orchestration policies in wide-area distributed systems such as Content Delivery Networks, Network Edge Fabric, Mobile Edge Computing, and IoT/Sensor Networks. He has published over 30 research papers in highly ranked conferences and journals. At Telstra, Dr. Pathan\’s key responsibility is to deliver architecture and technical solutions towards Telstra 2022 (T22) outcomes, specifically focusing on network abstraction, edge computing, automation, and 5G usecases. His core and extended teams develop Networks & IT transformation strategy, best practices, and foundational capabilities, e.g. Continuous Integration/Continuous Deployment (CI/CD), Test Automation framework, Self-Service Provisioning, Apps/VNF Architecture for Telco Edge Computing, Virtual Network Function (VNF) On-boarding, and ONAP Orchestration, in line with industry trends and customer expectations. He is a regular speaker in major industry forums and conferences.

Stamatis Karnouskos is with SAP in Germany, dealing with emerging industrial technologies and enterprise systems. He investigates the added value of integrating networked embedded devices and enterprise infrastructures. For more than 20 years Stamatis leads efforts in several European Commission and industry-funded projects related to industrial automation, smart grids, Internet/cloud-based services and architectures, software agents, security, and mobility. Findings have been published in several books and technical papers (see https://scholar.google.com/citations?user=WkLswkoAAAAJ). Stamatis has extensive experience on research and technology management within the industry, as well as with the European Commission and several national research funding bodies (e.g., in Germany, France, Switzerland, Denmark, Czech Republic, Greece, and Canada). He has served on the technical advisory board of Internet Protocol for Smart Objects Alliance (IPSO) and the Permanent Stakeholder Group of the European Network and Information Security Agency (ENISA). Stamatis is the chair of the IEEE IES Technical Committee on Industrial Agents as well as the IEEE IES Industry Activities Committee. He recently co-authored a book titled \”Internet of Things: Technologies and Applications for a New Age of Intelligence\” (Elsevier).

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