Collaborative Computing: Networking, Applications and Worksharing

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.

Klappentext

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.

Inhalt
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.