Recently, Mobile Edge Computing (MEC) has emerged as a significant computing paradigm, by enabling ubiquitous low-latency and on-demand access through Internet to edge/cloud applications. In this paradigm, edge computing platforms, infrastructures, and related communication frameworks are widely used as a service for performing data management, processing, and storage. Moreover, another technology trend that is recently gaining increased research attention from computing and communication researchers is in Artificial Intelligence and machine learning, which have the potential to demand low-latency in the emerging smart applications like smart user assistants, autonomous vehicles, and smart healthcare. The integration of Artificial Intelligence (AI) and mobile edge computing will unlock unprecedented possibilities in our day-to-day lives.
Mobile Edge Computing systems have diverse requirements based upon the use case, where it will rely on increased network connectivity for different sensors and communication devices. Since network scalability, reliability, and diversity are considered as critical requirements for mobile access networks like MEC, the 5G-driven communication is currently a key-enabler technology to overcome the challenges and manage the resources in a completely decentralized manner. In the light of aforementioned observations, there is a lack of security and privacy in the decentralized mobile edge computing environment. By deploying AI applications like machine learning in a decentralized manner, various data privacy and confidentiality attacks, adversarial attacks can be addressed. On the other hand, the deployment of deep learning, machine learning and other such algorithms will empower the edge architectures across different layers ranging from networking to applications.
The primary goal of this special section is to showcase research works from both academia and industry to present solutions to redesign the existing algorithms with different AI algorithms, like machine learning, for making it compatible to edge computing, and for deploying intelligent edge architectures. Also, this special section attempts to review and analyze a diverse range of features like reliability, security, privacy and trust in mobile edge computing. Additionally, it examines significant networking theories, computing and communication enablers that formulate novel mobile edge-driven application and the research submissions are expected to devise new methodologies and frameworks to overcome the major challenges possessed by AI-driven mobile edge computing frameworks.
Potential topics include:
Intelligent mobile edge computing systems and architecture
Network modelling and analysis techniques
Machine learning enabled communication and networking protocols for edge architecture
Novel resource management and optimization techniques
Big data management and analytics in edge-driven models
Distributed AI-driven algorithms for edge computing
Intelligent data pre-processing, analysis, and integration in MEC
Novel edge computing applications
AI-driven congestion-control and low-latency models for MEC
Scalability, security, privacy, and trust in AI-enabled MEC
Decentralized AI-enabled algorithms in MEC
Network attacks and its countermeasures in MEC applications
New papers, or extended versions of papers presented at related conferences, are welcome. Submissions must not be currently under review for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%), and must be referenced. All submitted papers will be peer-reviewed using the normal standards of CAEE, and accepted based on quality, originality, novelty, and relevance to the theme of the special section. By submitting a paper to this issue, the authors agree to referee one paper (if asked) within the time frame of the special issue. Before submission, authors should carefully read the Guide for Authors available at https://www.elsevier.com/journals/computers-and-electrical-engineering/0045-7906/guide-for-authors
Authors should submit their papers through the journal web submission tool at https://www.editorialmanager.com/compeleceng/default.aspx by selecting “VSI-aime” under the “Issues” tab.
For additional questions, contact the Main Guest Editor.
Manuscript submission: July 10, 2021
Acceptance Notification: August 10, 2021
Revised Manuscript Due: September 10, 2021
Second Review Completed: November 10, 2021
Final Manuscript Due: December 20, 2021
Publication: April 2022
Dr. A. Pasumpon Pandian (Managing Guest Editor)
Professor and Head, Department of CSE,
KGISL Institute of Technology,
Dr. Klimis Ntalianis
Professor, University of Applied Sciences
Dr. Ram Palanisamy
About the Guest Editors:
Dr. Pasumpon Pandian Arasu has received his Ph.D. degree in the Faculty of Information and Communication Engineering under Anna University, Chennai, TN, India in 2013. He received his graduation and post-graduation degree in Computer Science and Engineering from PSG College of Technology, Coimbatore, TN, India in the year 1993 and 2006 respectively. He is currently working as a Professor in the Computer Science and Engineering, Department of KGiSL Institute of Engineering and Technology, Coimbatore, TN, India. He has twenty-three years of experience in Teaching, Research, and IT industry. He has published more than 10 research articles in International Journals. Dr. Pandian has chaired and organized many IEEE and Springer International Conferences. His research interest includes Artificial intelligence, computing technologies, Behavioral analysis, and image processing.
Dr. Klimis Ntalianis received his diploma and Ph.D. degrees both from the Electrical and Computer Engineering Department of the National Technical University of Athens (NTUA) in 1998 and 2003 respectively. Between 2004 and 2006 he has written two Postdoctoral theses in the areas of multimedia protection and emotion analysis. From 1998 till 2009 he was a Senior Researcher and Projects Coordinator at the Image, Video and Multimedia Lab of NTUA. In parallel and from 2005 till 2011 he has worked as an adjunct lecturer at the University of Peloponnese, the Hellenic Naval Academy, the Hellenic Air Force and the Cyprus University of Technology. Dr. Ntalianis is an active reviewer of more than 10 International Journals of ΙΕΕΕ, Springer, Elsevier, etc. Additionally, he is an active reviewer and/or participates in the organizing committees of more than 10 International Conferences of ΙΕΕΕ, ΑCM, etc. From April 2015 he is an Associate Professor at the West Attica University. Dr. Ntalianis has participated as editor in the proceedings of 3 International Conferences, he has translated and was responsible for the scientific redaction of two Computer Science books (Kleidarithmos Publications), and he has written more than 150 scientific papers & deliverables and has received more than 650 citations. His main research interests include multimedia processing, social media analysis, crowdsourcing, and data mining.
Dr. Ram Palanisamy is a Full Professor in the Department of Information systems, Gerald Schwartz School of Business, St. Francis Xavier University, Nova Scotia. Dr. Ram has Thirty years of teaching, research, and consultancy in Information Systems Management. He joined StFX University in October 1999. Dr. Ram has successfully completed many Honours Thesis (INFO/ BSAD 498) Supervision. He has served as the chair and advisory committee Member for many International Conference. Dr. Ram’s primary teaching areas include Information Systems, E-Commerce, Database management, Business Information technology. He has edited 10 books/volumes for the refereed international journals. He was also associated as the editor and reviewer board member in various international journals. From 1995-present, he has published more than 5o research articles in various refereed proceedings of international conferences. Dr. Ram has over 50 publications in refereed international journals. Dr. Ram holds a Ph.D. from in Management Information Systems (MIS) planning from the Indian Institute of Technology (IIT), New Delhi, India and has undergone exclusive training courses at St. Francis Xavier University, Antigonish, Canada. His major research interests are in Information systems, data management, and knowledge management.