A Special Issue on: Scalable Dew Computing for future generation IoT systems
Introduction
Dew Computing (DC) as a new post-cloud computing model that enabling ubiquitous, pervasive, and convenient ready-to-go, plug-in facility empowered personal network that includes Single-Super-Hybrid-Peer P2P communication link. Dew Computing depends on a Dew–Fog–Cloud vertical scalable service hierarchy. Dew Computing performs several critical functions, such as device connectivity, protocol translation, data filtering and processing, security, updating, management, and more. Newer Dew Computing also operates as a platform for application codes that process data and become an intelligent part of an edge-device-enabled system. Dew Computing paradigm is envisaged to enhance current pervasive implementations in more flexible and distributed fashion. The area of such implementations is unlimited, that includes home automation, smart gardening, green computation, smart health care, traffic signal monitoring, context-aware communication, smart wearable computing, and industrial gas leakage monitoring. Out of all, IoT could play a major application role along with DC.
IoT is an application perspective model where heterogeneous devices act together to perform a set of tasks. Most of the time, aggregated data and inherent information are stored and extracted (respectively) in the allied cloud services. The Dew Computing allows functions to be executed on nearby devices found closer to the user, and the thing less approach goes even further, providing scalability on a low-level infrastructure that consists of multiple things, such as IoT devices. These approaches introduce the distribution of computing to other smart devices or things on a lower architectural level. Such an approach enhances the existing dew computing architectural model as a sophisticated platform for future generation IoT systems.
Recommended topics (but not limited to)
- Dew computing structure and architecture for IoT
- Dew computing for scalable mechanism such as Processor Utility and Data Storage on cloud
- Dew computing protocols and security for IoT
- Designing Communication protocols for IoT networks suitable to Dew computing
- Dew computing for peer-to-peer data management in IoT
- Horizontal scalable balancer for dew computing services
- Dew Recommender Engine for IoT applications
- Dew, Cloud and Fog computing integration for IoT
- Software-as-a-Dew Service for IoT devices
- Software-as-Dew Product for IoT products
Important dates
Submission deadline: 29 February, 2024
Authors notification: 31 March, 2024
Revision submission: 30 April, 2024
Completion of Special Issue: September, 2024
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
Dr. Mahesh T R (Managing Guest Editor) , Associate Professor, Department of Computer Science and Engineering, Jain University, Bangalore, India, email: maheshtr@ieee.org
MAHESH T R is working as an Associate Professor and Program Head in the Department of Computer Science and Engineering at Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bengaluru, India. Dr. Mahesh has to his credit more than 50 research papers in Scopus/WoS and SCIE indexed journals of high repute. He has been the editor for books on emerging and new age technologies with publishers like Springer, IGI Global, Wiley etc. Dr. Mahesh has served as reviewer and technical committee member for multiple conferences and journals of high reputation. He has also been a guest editor of several special issues including the journals like, International Journal of Intelligent Computing and Cybernetics, International Journal of e-Collaboration (IJeC), International Journal of Pervasive Computing and Communications(IJPCC), International Journal of System of Systems Engineering(IJSSE), Journal of Reliable Intelligent Environments (JRIE), International journal of Information Technology and Web Engineering (IJITWE),International Journal of Machine Learning and Computing (IJMLC),International Journal of Cloud Computing (IJCC),International Journal of Information Quality (IJIQ) ,Journal of Intelligent Enterprise (IJIE) etc.His research areas include image processing, machine learning, Deep Learning, Artificial Intelligence, IoT and Data Science.
Dr. Yudong Zhang, Professor, School of Computing and Mathematic Sciences, University of Leicester, UK , email: yudong.zhang@le.ac.uk
Dr. Yudong Zhang, serving as a professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. He worked as a postdoc from 2010 to 2012 with Columbia University, USA, and as an Assistant Research Scientist from 2012 to 2013 with the Research Foundation of Mental Hygiene (RFMH), USA. He served as a Full Professor from 2013 to 2017 with Nanjing Normal University. His research interests include deep learning and medical image analysis. He is the Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was included in Most Cited Chinese Researchers (Computer Science) by Elsevier from 2014 to 2018. He was the 2019, 2021 & 2022 recipient of Highly Cited Researcher by Clarivate. He won the Emerald Citation of Excellence 2017 and MDPI Top 10 Most Cited Papers 2015. He is included in Top Scientist in Research.com. He has (co)authored over 400 peer-reviewed articles in the journals JAMA Psychiatry, Inf Fus, IEEE TFS, IEEE TII, IEEE TIP, IEEE TMI, IEEE IoTJ, Neural Networks, IEEE TITS, Pattern Recognition, IEEE TGRS, IEEE JBHI, IEEE TCSVT, IEEE TETCI, IEEE TCSS, IEEE JSTARS, IEEE TNSRE, IEEE Sensors J, ACM TKDD, ACM TOMM, IEEE/ACM TCBB, IEEE TCAS-II, IEEE JTEHM, ACM TMIS, etc. There are more than 50 ESI Highly Cited Papers and 5 ESI Hot Papers in his (co)authored publications.
Dr. Polinpapilinho F.Katina, Department of Informatics and Engineering Systems, University of South Carolina Upstate, USA, email: pkatina@uscupstate.edu
Polinpapilinho F. Katina is working as Professor in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate (Spartanburg, South Carolina, USA). He previously served as a Postdoctoral Researcher for the National Centers for System of Systems Engineering (Norfolk, Virginia, USA) and Adjunct Professor in the Department of Engineering and Systems Engineering at Old Dominion University (Norfolk, Virginia, USA). Dr. Katina holds a B.Sc. in Engineering Technology with a minor in Engineering Management, a M.Eng. in Systems Engineering and a Ph.D. in Engineering Management/Systems Engineering, all from Old Dominion University (Norfolk, Virginia, USA). He has received additional training from, among others, Environmental Systems Research Institute (Redlands, California) and Politecnico di Milano (Milan, Italy). He is a editorial member of various journals, Complex System Governance, Critical Infrastructure Systems, Decision Making and Analysis (under uncertainty), Emerging Technologies, Energy Systems (Smart Grids), Engineering Management, Infranomics, Manufacturing Systems, System-of-Systems, Systems Engineering, Systems pathology, and Systems Thinking. Dr. Katina’s profile includes more than 150 scholarly outputs in the form of peer-reviewed journal articles, conference proceedings, book chapters and books. Other highlights include: Named in the top 1% for the 2018 Publons Global Peer Review Awards, Serving as a Guest Editor for the International Journal of Critical Infrastructures (2014), Serving as a Guest Editor for the International Journal of System of Systems Engineering (2015), Panellist for the 2017 National Defense Science and Engineering Graduate Fellowship, Panel list for the 2019 National Defense Science and Engineering Graduate Fellowship, Founding board member for the International Society for Systems Pathology (Claremont, California), Course developer (2018 – 2019) of four new courses in a newly formed program at the University of South Carolina Upstate.
Published in 2024
- Crop Field Boundary Detection and Classification using Machine Learning
- Hybrid Architecture Strategies for the Prediction of Acute Pulmonary Embolism from Computed Tomography Images
- Modeling a Smart IoT Device for Monitoring Indoor and Outdoor Atmospheric Pollution
- Application of Improving ABC in Cold Chain Low Carbon Logistics Path Planning
- Secure Steganography Model over Cloud Environment using Adaptive ABC and Optimum Pixel Adjustment Algorithm
- Vulnerability Detection in Cyber-Physical System Using Machine Learning
- Novel Authenticated Strategy for Security Enhancement in VANET System using Block Chain Assisted Novel Routing Protocol
- An Elixir for Blockchain Scalability with Channel based Clustered Sharding
- Feature Extraction and Classification of Gray-Scale Images of Brain Tumor using Deep Learning
- A Class Specific Feature Selection Method for Improving the Performance of Text Classification
- Breast Cancer Image Classification based on Adaptive Interpolation Approach Using Clinical Dataset
- SecureSense: Enhancing Person Verification through Multimodal Biometrics for Robust Authentication
- Radiogenomics in Oncology
- Sensor based Dance Coherent Action Generation Model using Deep Learning Framework
- IoT based Dance Movement Recognition Model based on Deep Learning Framework
- A Lightweight Symmetric Cryptography based User Authentication Protocol for IoT based Applications
- Scalable Video Fidelity Enhancement: Leveraging the state-of-the-art AI Models
- Optimised ResNet50 for Multi-Class Classification of Brain Tumors
- Localization of Dielectric Anomalies with Multi-level Outlier Detection through Membership Function and Ensemble Classification Framework
- SCHeMoS -- Smart Cow Health Monitoring System: An IoT based Cow Hoof Detection and Healthcare Alert System by Using LSTM Network
- Performance Analysis for Optimized Light Weight CNN Model for Leukemia Detection and Classification using Microscopic Blood Smear Images
- IoT-Driven Hybrid Deep Collaborative Transformer with Federated Learning for Personalized E-Commerce Recommendations: An Optimized Approach
- Brain Tumor Classification using Region-based CNN with Chicken Swarm Optimization
- Improving Data Security and Scalability in Healthcare System using Blockchain Technology
- Enhanced Throttled Load Balancing for Virtual Machine Allocation in Multiple Data Centers
- Design and Development of an Unmanned/Autonomous Ocean Surface Vehicle using Self-Sustaining Dual Renewable Energy Harvesting System
- Scalable Innovative Factors for Shaping Consumer Intentions on Electric Two-Wheelers Adoptions
- Identifying Crop Distress and Stress-Induced Plant Diseases Using Hyper Spectral Image Analysis
- An Improved Hyper Spectral Imaging for Accurate Disease Diagnosis in Sustainable Medical Environments
- Enhancing Black Hole Attack Detection in VANETs: A Hybrid Approach Integrating DBSCAN Clustering with Decision Trees
- Optimizing Hadoop Data Locality: Performance Enhancement Strategies in Heterogeneous Computing Environments
- Federated Diverse Self-ensembling Learning Approach for Data Heterogenity in Drive Vision
- Machine Learning based Lung Cancer Diagnostic System using Optimized Feature Subset Selection