Collaborative Computing: Networking, Applications and Worksharing

19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part III

Häftad, Engelska, 2024

Del 563 i serien Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Beskrivning

The three-volume set LNICST 561, 562 563 constitutes the refereed post-conference proceedings of the 19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023, held in Corfu Island, Greece, during October 4-6, 2023.The 72 full papers presented in these proceedings were carefully reviewed and selected from 176 submissions. The papers are organized in the following topical sections:Volume I : Collaborative Computing, Edge Computing & Collaborative working, Blockchain applications, Code Search and Completion, Edge Computing Scheduling and Offloading.Volume II: Deep Learning and Application, Graph Computing, Security and Privacy Protection and Processing and Recognition.Volume III: Onsite Session Day2, Federated learning and application, Collaborative working, Edge Computing and Prediction, Optimization and Applications.

Produktinformation

Utgivningsdatum:2024-02-23
Mått:155 x 235 x 23 mm
Vikt:639 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Antal sidor:408
Förlag:Springer International Publishing AG
ISBN:9783031545306

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Innehållsförteckning

Onsite Session Day 2.- Multi-agent Reinforcement Learning based Collaborative Multi-task Scheduling for Vehicular Edge Computing.- A Novel Topology Metric for Indoor Point Cloud SLAM Based on Plane Detection Optimization.- On the Performance of Federated Learning Network.- Federated learning and application.- FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification.- CSA_FedVeh: Cluster-based Semi-Asynchronous Federated Learning framework for Internet of Vehicles.- Efficiently Detecting Anomalies in IoT: A Novel Multi-Task Federated Learning Method.- A Novel Deep Federated Learning-based and Profit-Driven Service Caching Method.- A Multi-Behavior Recommendation Algorithm Based on Personalized Federated Learning.- FederatedMesh: Collaborative Federated Learning for Medical Data Sharing in Mesh Networks.- Collaborative working.- Enhance broadcasting throughput by associating network coding with UAVs relays deployment in emergency communications.- Dynamic Target User Selection Model For Market Promotion with Multiple Stakeholders.- Collaborative Decision-making Processes Analysis of Service Ecosystem: A Case Study of Academic Ecosystem Involution.- Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical Guidelines.- Enriching Process Models with Relevant Process Details for Flexible Human-Robot Teaming.- Edge Computing.- Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems.- Enhancing Session-based Recommendation with Multi-granularity User Interest-aware Graph Neural Networks.- Delay-constrained Multicast Throughput Maximization in MEC Networks for High-Speed Railways.- An Evolving Transformer Network based on Hybrid Dilated Convolution for Traffic Flow Prediction.- Prediction, Optimization and Applications.- DualDNSMiner: A Dual-stack Resolver Discovery Method Based on Alias Resolution.- DT-MUSA: Dual Transfer Driven Multi-Source Domain Adaptation for WEEE Reverse Logistics Return Prediction.- A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning.