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Collaborative Computing: Networking, Applications and Worksharing 19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part I

Aus der Reihe Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Beschreibung

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...

Beschreibung

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.

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

23.02.2024
Abbildungen

XXI, 444 p. 162 illus., 140 illus. in color.
Herausgeber Honghao Gao + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

23.02.2024
Abbildungen

XXI, 444 p. 162 illus., 140 illus. in color.
Herausgeber
Verlag Springer
Seitenzahl

444
Maße (L/B/H)

23,5/15,5/2,6 cm
Gewicht

703 g
Auflage

2024
Sprache

Englisch
ISBN

978-3-031-54520-7
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Collaborative Computing: Networking, Applications and Worksharing
  • Produktbild: Collaborative Computing: Networking, Applications and Worksharing
  • Collaborative Computing .- Enhanced Sound Recognition and Classification through Spectrogram Analysis, MEMS Sensors, and PyTorch: A Comprehensive Approach.- TCP Cubic Implementation in the OMNeT++ INET Framework for SIoT Simulation Scenarios.- Implementation Framework of a Blockchain Based Infrastructure for Electricity Trading within a Microgrid.- Resource Cooperative Scheduling Optimization Considering Security in Edge Mobile Networks.-  Edge Computing & Collaborative working .- DQN-based Applications Offloading with Multiple Interdenpendent Tasks in Mobile Edge Computing.- Edge Server Deployment Approach Based on Uniformity and Centrality.- Budget-constrained Contention-aware Workflow Scheduling in a Hybrid Cloud.- A Dichotomous Repair-based Load-Balanced Task Allocation Strategy in Cloud-Edge Environment.- DPIM: Dynamic Pricing Incentive Mechanism for Mobile Crowd Sensing.-  Blockchain applications .- Efficient and revocable anonymous account guarantee system based on blockchain.- Computing Resource Allocation for Hybrid Applications of Blockchain and Mobile Edge Computing.- Blockchain-Based EMR Enhancement: Introducing PMI-Chain for Improved Medical Data Security and Privacy.- BGET: A Blockchain-based Grouping-EigenTrust Reputation Management Approach for P2P Networks.- Privacy-Preserving Blockchain Supervision with Responsibility Tracking.-  Code Search and Completion .- JARAD: An Approach for Java API Mention Recognition and Disambiguation in Stack Overflow.- Enrich Code Search Query Semantics With Raw Descriptions.- A code completion approach combining pointer network and Transformer-XL network.- A Code Search Method Incorporating Code Annotations.- CUTE A Collaborative Fusion Representation-based Fine-tuning and Retrieval Framework for CodeSearch.-  Edge Computing Scheduling and Offloading .- Roadside IRS Assisted Task Offloading in Vehicular Edge Computing Network.- Collaborative Task Processing and Resource Allocation Based on Multiple MEC Servers.- Collaborative Cloud-Edge Computing with Mixed Wireless and Wired Backhaul Links: Joint Task Offloading and Resource Allocation.- Dynamic offloading based on meta deep reinforcement learning and load prediction in smart home edge computing.