Collaborative Computing: Networking, Applications and Worksharing

18th EAI International Conference, CollaborateCom 2022, Hangzhou, China, October 15-16, 2022, Proceedings, Part I
1. Auflage 2023
ISBN: 978-3-031-24382-0
Verlag: Springer

Buch, Englisch, Band 460, 555 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 861 g

Reihe: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

The two-volume set LNICST 460 and 461 constitutes the proceedings of the 18th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2022, held in Hangzhou, China, in October 2022. 
The 57 full papers presented in the proceedings were carefully reviewed and selected from 171 submissions. The papers are organized in the following topical sections: Recommendation System; Federated Learning and application; Edge Computing and Collaborative working; Blockchain applications; Security and Privacy Protection; Deep Learning and application; Collaborative working; Images processing and recognition.

Zielgruppe

Research

Autoren/Hrsg.

Gao, Honghao

Wang, Xinheng

Wei, Wei

Dagiuklas, Tasos

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Recommendation System.-  A Negative Sampling-based Service Recommendation Method.- Knowledge Graph Enhanced Web API Recommendation via Neighbor Information Propagation for Multi service Application Development.- Expertise-oriented Explainable Question Routing.- An API Recommendation Method based on Beneficial Interaction.- A flow prediction model of bike-sharing based on cycling context.-  Federated Learning and application.-  FedFR: Evaluation and Selection of Loss Functions for Federated Face Recognition.- FedCL: An Efficient Federated Unsupervised Learning for Model Sharing in IoT.- Edge Federated Learning for Social Profit Optimality: A Cooperative Game Approach.- MetaEM: Meta Embedding Mapping for Federated Cross-Domain Recommendation to Cold-Start Users.- A Reliable Service Function Chain Orchestration Method Based on Federated Reinforcement Learning.-  EdgeComputing and Collaborative working.-  A Context-aware Approach to Scheduling of Multi-Data- Source Tasks in Mobile Edge Computing.- Secure and Private Coding for Edge Computing against Cooperative Attack with Low Communication Cost and Computational Load.- Availability-Constrained Application Deployment in Hybrid Cloud-Edge Collaborative Environment.- EBA: An Adaptive Large Neighborhood Search-based Approach for Edge Bandwidth Allocation.- System Completion Time Minimization with Edge Server Onboard Unmanned Vehicle.- An approach to the synchronization of dynamic complex network combining degree distribution and eigenvector criteria.- An Energy-Saving Strategy for 5G Base Stations in Vehicular Edge Computing.- An efficient scheduling strategy for containers based on Kubernetes.- NOMA-Based Task Offloading and Allocation in Vehicular Edge Computing Networks.- A Collaborative Graph Convolutional Networks and Learning Styles Model For Courses Recommendation.- Exploring the Impact of Structural Holes on the Value Creation in Service Ecosystems.- Learning Dialogue Policy Efficiently Through Dyna Proximal Policy Optimization.- Self-Gated FM: Revisiting the Weight of Feature Interactions for CTR Prediction.- Heterogeneous Graph Neural Network-based Software Developer Recommendation.-  Blockchain applications.-  FAV-BFT:An Efficient File Authenticity Verification Protocol for Blockchain-based File-Sharing System.- Incentive Mechanism Design for Uncertain Tasks in Mobile Crowd Sensing Systems Utilizing Smart Contract in Blockchain.- Research on the Update Method of CP-ABE Access Control Strategy based on Smart Contract.- Effective Blockchain-based Asynchronous Federated Learning for Edge-computing.- One-Time Anonymous Certificateless Signcryption Scheme Basedon Blockchain.