Collaborative Computing: Networking, Applications and Worksharing (eBook, PDF)

20th EAI International Conference, CollaborateCom 2024, Wuzhen, China, November 14-17, 2024, Proceedings, Part I
Redaktion: Gao, Honghao; Wang, Xinheng

• Format: PDF

Produktbeschreibung

The three-volume set LNICST 624, 625, 626 constitutes the refereed proceedings of the 20th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2024, held in Wuzhen, China, during November 14-17, 2024.

The 62 full papers were carefully reviewed and selected from 173 submissions. They are categorized under the topical sections as follows:

Edge computing & Task scheduling

Deep Learning and application

Blockchain applications

Security and Privacy Protection

Representation learning & Collaborative working

Graph neural networks & Recommendation systems

Federated Learning and application

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 494
• Erscheinungstermin: 9. August 2025
• Englisch
• ISBN-13: 9783031932519
• Artikelnr.: 75154040

Inhaltsangabe

Edge Computing & Task Scheduling.- Latency Energy aware Heterogeneous Resource Allocation and Task Scheduling in Industrial Cloud Edge Computing.- Backpressure-based Federated Learning Model Scheduling in Edge Computing.- Minimizing the Age of Knowledge in Application-oriented Mobile Edge Computing System with DRL-based Scheduling.- Dependency-Aware Task Offloading in Dynamic Network Environment with D2D Collaboration.- Delay Minimization for Downlink PD-NOMA Transmission with Index Coding in Cache-Aided Wireless Networks.- Fast Adaptive Caching Algorithm for Mobile Edge Networks Based on Meta-Reinforcement Learning.- Delay- and Cost-Aware Dynamic Service Migration in Collaborative Satellite Computing.- Towards Efficient Scheduling in Large Clusters Leveraging the Small-World Network Model.- A Dynamic Prioritization Task Offloading Strategy with Delay Constraints.- Task Scheduling Strategy among Multiple Local Mobile Clouds in Pervasive Edge Computing.- A Task Scheduling Strategy Based on Computing-Aware and Multi-Agent Collaborative Services in Pervasive Edge Computing.- Collaborative Vehicular Edge Cloud Computing Task Offloading Optimization Scheme Based on Deep Reinforcement Learning.- Deep Learning and Application.- NL-ATD: Spatio-Temporal Few-Shot Learning via Attention Transfer and Denoising Model.- A GCN-based DRL Approach for task migration and resource allocation in Heterogeneous Edge-Cloud Environments.- A Multi-Document Summarization Method for Customer Feedback Based on Large Language Models.- KaRe: Towards Flexible and Effective Machine Unlearning with Knowledge Alignment and Repair.- SWGCNN-BiLSTM: A Method for Detecting Unknown Attack Traffic within Imbalanced Samples.- Two-stage workflow scheduling based on deep reinforcement learning.- GRASP-SLAM: Gmapping-augmented DRL for Active SLAM using Policy gradient.- WiLDID:Low-Collaboration WiFi-Based Person Identification Via A Lightweight Deep Neural Network.- Dialogue Summarization by Integrating Structural Features and Improving Factual Consistency through Post-Editing.- TransAware: An Automatic Parallel Method for Deep Learning Model Training with Global Model Structure Awareness.- A Reliability Enhancement Scheme for Distributed Cloud Service Systems Based on Deep Reinforcement Learning.- Contrastive Learning-Based Finger-Vein Recognition Using Frequency-Mixup Augmentation and Time-Frequency Feature Fusion.- BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction.