Collaborative Computing: Networking, Applications and Worksharing

Chapter 1 Multi-agent Reinforcement Learning Based Collaborative Multi-task Scheduling for Vehicular Edge Computing

Chapter 2 A Novel Topology Metric for Indoor Point Cloud SLAM Based on Plane Detection Optimization

Chapter 3 On the Performance of Federated Learning Network

Chapter 4 FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification

Chapter 5 CSA_FedVeh: Cluster-Based Semi-asynchronous Federated Learning Framework for Internet of Vehicles

Chapter 6 Efficiently Detecting Anomalies in IoT: A Novel Multi-Task Federated Learning Method

Chapter 7 A Novel Deep Federated Learning-Based and Profit-Driven Service Caching Method

Chapter 8 A Multi-behavior Recommendation Algorithm Based on Personalized Federated Learning

Chapter 9 FederatedMesh: Collaborative Federated Learning for Medical Data Sharing in Mesh Networks

Chapter 10 Enhance Broadcasting Throughput by Associating Network Coding with UAVs Relays Deployment in Emergency Communications

Chapter 11 Dynamic Target User Selection Model for Market Promotion with Multiple Stakeholders

Chapter 12 Collaborative Decision-Making Processes Analysis of Service Ecosystem: A Case Study of Academic Ecosystem Involution

Chapter 13 Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical Guidelines

Chapter 14 Enriching Process Models with Relevant Process Details for Flexible Human-Robot Teaming

Chapter 15 Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems

Chapter 16 Enhancing Session-Based Recommendation with Multi-granularity User Interest-Aware Graph Neural Networks

Chapter 17 Delay-Constrained Multicast Throughput Maximization in MEC Networks for High-Speed Railways

Chapter 18 An Evolving Transformer Network Based on Hybrid Dilated Convolution for Traffic Flow Prediction

Chapter 19 DualDNSMiner: A Dual-Stack Resolver Discovery Method Based on Alias Resolution

Chapter 20 DT-MUSA: Dual Transfer Driven Multi-source Domain Adaptation for WEEE Reverse Logistics Return Prediction

Chapter 21 A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning