A Special Issue on: Efficient Scalable Computing based on IoT and Cloud Computing

Introduction

Due to the interconnectivity of the Internet of Things (IoT) and the high stability and reliability of cloud computing, the IoT and cloud computing play a vital role in modern information and computing technology. However, managing the heterogeneous data generated by IoT devices can be challenging as it requires significant storage, processing power, and the use of modern, efficient design and implementation techniques. In most cases, the key to overcoming this challenge is cloud computing. Cloud computing can provide a large amount of computing power and storage space for IoT, enabling IoT to perform advanced data processing and analysis to obtain more valuable information. In addition, scalability is a critical means of contemporary and future computing systems and becomes one of the most important considerations during the design and deployment of systems. Scalable computing involves using a computer system that can adapt to enormous advanced computing capabilities. Scalable computing based on IoT and cloud computing enables large-scale data processing and real-time analysis.

Although many studies have been carried out by researchers in industry and academia, with the rapid increase of information volume and system complexity, new architectures and techniques are needed to support scalable computing. A number of current challenges include: how to effectively and efficiently handle the massive data generated by IoT devices? How to develop the foundational architecture and platform to support the efficient and scalable processing of hybrid data sets? How to handle the heterogeneity of physical network devices, Security privacy and scalability etc. Therefore, this special issue aims to encourage experts and scholars to discuss and explore the latest research on various aspects of efficient scalable computing based on IoT and cloud computing, as well as its applications and challenges. We invite researchers to submit a contribution in the form of an original scientific research article for this Special Issue.

Recommended topics (but not limited to)

  • Granular computing and engineering data processing
  • Scalability analysis of parallel computing
  • Blockchain technology in mobile edge computing
  • Applications of scalable computing and data analytics in the IoT
  • Architecture design for the cloud computing and IoT
  • Scalable computing infrastructure for cloud computing and IoT
  • Performance, reliability and scalability of IoT systems
  • Security, privacy, and scalability of cloud-based IoT computing approaches
  • Parallel and Distributed Models for Cyber-Physical Systems
  • Scalable Platforms and Advanced Algorithms for IoT and cloud computing
  • Architecture, algorithm and software for cloud-edge-IoT orchestration and continuum

Important dates

Submission deadline: 30 June, 2024

Authors notification: 31 October, 2024

Revision submission: 31 December, 2024

Completion of Special Issue: March, 2025

Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.

During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

Guest Editors

Lead: Dr. Jingsha He , Professor, Faculty of Information Technology, Beijing University of Technology, China, email: jsh.bjut@gmail.com

Prof. Jingsha He graduated from University of Maryland, and has worked in IBM Corp., MCI Communications Corp., GRIC Communications, Inc., etc. in America, and got 15 American patents for inventions. In 2003, he was introduced to Beijing University of Technology. At present, he has published 261 papers in international journals and conference proceedings, of which Has been indexed by SCI/EI/ISTP more than 180 articles; published 4 textbooks or professional technical books, 3 translations, and got 58 Chinese patents for invention, presided over more than 30 projects as well, such as National Natural Science Foundation of China, 863 project, etc. He serves as the Editor-in-chief for Journal of Simulation, and the lead guest editor for Special Issues published in over 12 journals including IEEE Transactions on Intelligent Transportation Systems (IF: 6.319), Sensors (IF: 3.847), and so on. He also serves as the reviewer for Computer Standards & Interfaces, Computational Visual Media, Journal of Network and Systems Management, International Journal of Sensor Networks, Digital Investigation, International Journal of Computational Intelligence Systems, International Journal of Distributed Sensor Networks, Journal on Wireless Communications and Networking, Computer Communications, etc. His research interests span the field of computer networks, computer vision, information safety, big data and cloud computing security, deep learning, etc. He has given over 50 invited talks at international conferences, universities, and companies. He has served as General Chair/Co-Chair for more than 20 international conferences and workshops.

Dr. Xiaodong Liu, Professor, Head of Intelligence-Driven IoT and Smart Systems Research Group, UK, email: X.Liu@napier.ac.uk

Prof. Xiaodong Liu has been very active in the research in AI-driven software engineering, focusing on pervasive systems (Internet of Things), service-oriented architecture, evolution of cloud services, and intelligence-driven smart systems. He has won 12 external grants and successfully led or leading these externally funded projects with the role of principal investigator. Currently Prof. Liu leads the Intelligence-Driven IoT and Smart Systems Research Group. He is the founder a spin out company, FlexiCAGE Ltd. He has published 175 papers in refereed international journals and conferences and 5 book chapters. He is the inventor of 1 patent in Generative Component Adaptation registered in UK, USA and at International Level (PCT). He has been the chair, co-chair or PC member of a number of IEEE and ACM International Conferences. He is the associate editor of 2 international journals and the editorial board member of 3 international journals. He is the chief editor of 3 IGI Global Research Handbooks and the editor of 5 journal special issues. He has given 15 keynote talks at international conferences. He is a senior member of IEEE Computer Society, and a member of British Computer Society.

Dr. Sos Agaian, Professor, College of Staten Island and the Graduate Center, City University of New York, USA, email: Sos.Agaian@csi.cuny.edu

Sos Agaian is a Distinguished Professor of Computer Science at College of Staten Island and the Graduate Center, CUNY. Prior to joining the City University of New York, Dr. Agaian was a Peter T. Flawn Professor of Electrical and Computer Engineering with the University of Texas at San Antonio. His main research interests are in Computational Vision and Machine Learning, Big and Small Data Analytics, Multimodal Biometric and Digital Forensics. He has authored over 600 peer-reviewed research papers, ten books, and nineteen edited proceedings. He is listed as a co-inventor on 44 patents/disclosures. Dr. Agaian was elected IEEE Fellow, SPIE Fellow. Dr. Agaian received his M.S. degree (summa cum laude) in Mathematics and Mechanics from Yerevan State University, Armenia; his Ph.D. in Mathematics and Physics from the Steklov Institute of Mathematics, Russian Academy of Sciences (RAS); and his Doctor of Engineering Sciences degree from the Institute of Control Systems, RAS.

Published in 2024