Dynamic Task Allocation and Service Migration in Edge-Cloud IoT System based on Deep Reinforcement Learning
Edge computing extends the ability of cloud computing to the network edge to support diverse resource-sensitive and performance-sensitive IoT applications. However due […]
A Novel Internet-of-Drones and Blockchain-based System Architecture for Search and Rescue
With the development in information and communications technology (ICT) and drones such as Internet-of-Things (IoT), edge computing, image processing, and autonomous drones, […]
Edge Intelligence
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data […]
Fast MIMO Beamforming via Deep Reinforcement Learning for High Mobility mmWave Connectivity
Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves) where fast and efficient beamforming is vital for providing continuous service […]
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels
Today’s intelligent applications can achieve high performance accuracy using machine learning (ML) techniques, such as deep neural networks (DNNs). Traditionally, in a […]
CAD3
Speeding, slowing down, and sudden acceleration are the leading causes of fatal accidents on highways. Anomalous driving behavior detection can improve road […]
5G Edge Computing Enhanced Mobile Augmented Reality
Physical world enhancements through virtually drawn annotations on mobile devices are a core component of mobile augmented reality (MAR) experiences. However, resource […]
Health-BlockEdge
The rapid evolution of technology allows the healthcare sector to adopt intelligent, context-aware, secure, and ubiquitous healthcare services. Together with the global […]
EDISON
Spatio-temporal interpolation provides estimates of observations in unobserved locations and time slots. In smart cities, interpolation helps to provide a fine-grained contextual […]
Concept Drift Adaptation Techniques in Distributed Environment for Real-World Data Streams
Real-world data streams pose a unique challenge to the implementation of machine learning (ML) models and data analysis. A notable problem that […]