Area of research
Computer Networks and Communications · Information Systems
Research interest
Research interests include Cloud Computing and Resource Management, Distributed and Parallel Computing Systems, IoT and Edge/Fog Computing, and Parallel Computing and Optimization Techniques.
Remote sensing revolutionizing agriculture: Toward a new frontier
Container Scheduling Strategy Based on Image Layer Reuse and Sequential Arrangement in Mobile Edge Computing
Cloud-Native Computing: A Survey From the Perspective of Services
TrustBCFL: Mitigating Data Bias in IoT Through Blockchain-Enabled Federated Learning
MC-DSC: A Dynamic Secure Resource Configuration Scheme Based on Medical Consortium Blockchain
Overtaking Feasibility Prediction for Mixed Connected and Connectionless Vehicles
Game Theory Based Optimal Defensive Resources Allocation with Incomplete Information in Cyber-Physical Power Systems Against False Data Injection Attacks
Dynamic multi-scale spatial–temporal graph convolutional network for traffic flow prediction
FedGCN: A Federated Graph Convolutional Network for Privacy-Preserving Traffic Prediction
Quantum social network analysis: Methodology, implementation, challenges, and future directions
Novel Lagrange Multipliers-Driven Adaptive Offloading for Vehicular Edge Computing
psvCNN: A Zero-Knowledge CNN Prediction Integrity Verification Strategy
The Analysis and Optimization of Volatile Clients in Over-the-Air Federated Learning
Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions
An explainable deep learning-enabled intrusion detection framework in IoT networks
Lightweight Remote Sensing Change Detection With Progressive Feature Aggregation and Supervised Attention
MESON: A Mobility-Aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing
Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities
A Novel Federated Learning Scheme for Generative Adversarial Networks
GriDB: Scaling Blockchain Database via Sharding and Off-Chain Cross-Shard Mechanism
An Autonomic Workload Prediction and Resource Allocation Framework for Fog-Enabled Industrial IoT
Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning
Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering
Energy-Aware, Device-to-Device Assisted Federated Learning in Edge Computing
Multi-graph fusion based graph convolutional networks for traffic prediction
Validating the integrity of Convolutional Neural Network predictions based on zero-knowledge proof
Towards Real-Time Inference Offloading With Distributed Edge Computing: The Framework and Algorithms
Automatic Software Tailoring for Optimal Performance
AI-Enabled Secure Microservices in Edge Computing: Opportunities and Challenges
Stochastic Client Selection for Federated Learning With Volatile Clients