Collection
Machine Learning at the Edge for the Cloud Continuum
This special issue focuses on theoretical and practical approaches to developing and deploying Machine Learning algorithms successfully at the smart edge devices with the High-Performance Edge Computing models, which are capable of executing computationally intensive applications more efficiently.
Editors
-
Dr. Soheil Salahshour
Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey.
-
Dr. Bruno Antonio Pansera
Department of Law, Economics and Human Sciences, Mediterranea University of Reggio Calabria, Reggio Calabria, Italy
-
Dr. Ashutosh Dhar Dwivedi
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
Articles (60 in this collection)
-
-
Exploring the Synergy of Blockchain, IoT, and Edge Computing in Smart Traffic Management across Urban Landscapes
Authors (first, second and last of 6)
-
-
Multi-Agent Systems for Collaborative Inference Based on Deep Policy Q-Inference Network
Authors (first, second and last of 4)
-
-
-
Joint Task Offloading Based on Distributed Deep Reinforcement Learning-Based Genetic Optimization Algorithm for Internet of Vehicles
Authors (first, second and last of 5)
-
Employing RNN and Petri Nets to Secure Edge Computing Threats in Smart Cities
Authors (first, second and last of 5)
-
Edge Computing Empowered Smart Healthcare: Monitoring and Diagnosis with Deep Learning Methods
Authors (first, second and last of 4)
-
-
-
-
An IoT-based Covid-19 Healthcare Monitoring and Prediction Using Deep Learning Methods
Authors (first, second and last of 4)
-
Smart City Transportation: A VANET Edge Computing Model to Minimize Latency and Delay Utilizing 5G Network
Authors (first, second and last of 8)
-
-
A Federated Deep Reinforcement Learning-based Low-power Caching Strategy for Cloud-edge Collaboration
Authors (first, second and last of 7)
-
-
-
-
3D Lidar Target Detection Method at the Edge for the Cloud Continuum
Authors (first, second and last of 4)
-
-
-
-
-
Novel Transformation Deep Learning Model for Electrocardiogram Classification and Arrhythmia Detection using Edge Computing
Authors (first, second and last of 6)
-
-
-
-
DEEPBIN: Deep Learning Based Garbage Classification for Households Using Sustainable Natural Technologies
Authors (first, second and last of 8)
-
Markovian with Federated Deep Recurrent Neural Network for Edge—IoMT to Improve Healthcare in Smart Cities
Authors (first, second and last of 4)
-
Healthcare and Fitness Services: A Comprehensive Assessment of Blockchain, IoT, and Edge Computing in Smart Cities
Authors (first, second and last of 4)
-
Integration of a Lightweight Customized 2D CNN Model to an Edge Computing System for Real-Time Multiple Gesture Recognition
Authors (first, second and last of 4)
-
-
-
-
Sustainable Environmental Design Using Green IOT with Hybrid Deep Learning and Building Algorithm for Smart City
Authors (first, second and last of 6)
-
Secured SDN Based Task Scheduling in Edge Computing for Smart City Health Monitoring Operation Management System
Authors (first, second and last of 5)
-
Hybrid Immune Whale Differential Evolution Optimization (HIWDEO) Based Computation Offloading in MEC for IoT
Authors (first, second and last of 4)
-
-
-
Anti-Attack Intrusion Detection Model Based on MPNN and Traffic Spatiotemporal Characteristics
Authors (first, second and last of 5)
-
Honeypot Based Industrial Threat Detection Using Game Theory in Cyber-Physical System
Authors (first, second and last of 4)
-
-
Image Fuzzy Edge Information Segmentation Based on Computer Vision and Machine Learning
Authors (first, second and last of 10)
-
-
-
A Load-Aware Energy-Efficient Clustering Algorithm in Sensor-Cloud
Authors (first, second and last of 4)
-
Adaptive Terrain Spider UWB Following Delivery Robot Based on Spring Suspension and Edge Computing
Authors (first, second and last of 4)
-
A Federated Framework for Edge Computing Devices with Collaborative Fairness and Adversarial Robustness
Authors (first, second and last of 4)
-
A Heuristic Deep Q Learning for Offloading in Edge Devices in 5 g Networks
Authors (first, second and last of 5)
