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E-raamat: Collaborative Computing: Networking, Applications and Worksharing: 21st EAI International Conference, CollaborateCom 2025, Shanghai, China, November 15-16, 2025, Proceedings, Part II

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This two-volume set LNICST 680-681 constitutes the refereed proceedings of the 21st EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2025, held in Shanghai, China, during November 1516, 2025.



The 58 full papers included in these volumes were carefully reviewed and selected from 207 submissions. They are categorized under the topical sections as follows:  



Part I: Large Language Models & Recommendation systems; and Deep Learning and application. Part II: Federated Learning & Collaborative working; Edge computing & Task scheduling; Security and Blockchain applications; and Anomaly Detection.
.- Federated Learning & Collaborative working.
.- A Data Fusion Processing Architecture for Multi-Node Network Cooperative
Integrated Sensing and Communication.
.-  Robustness Analysis of Multi-layer LEO Satellite Networks with Dynamic
Heterogeneous Cascading Failure Model.
.- AC-KVS: Adaptive Centralized Key-Value Scheduler in Programmable Switch
for Distributed Key-value Stores.
.- FedSTAR: A Federated Learning Framework for Reliable Trajectory Prediction
under Spatiotemporal Heterogeneity.
.- A Hierarchical Model of Trusted Federation Based on Adaptive Mutual
Learning.
.- A Service-Oriented Adaptive Hierarchical Incentive Solution for Federated
Learning.
.- Correlation Aware Imbalanced Multimodal Fusion in IoT Environment.
.- Trust-Aware UAV-Vehicle Hierarchical Collaboration for Efficient
Multimedia Big Data Collection.
.- PVA-FL: Practical Verifiable Aggregation for Privacy Preserving Federated
Learning.
.-  H2A-BPMN: A Hierarchical & Hybrid Agent Framework for Industrial BPMN
Automated Modeling.
.- LADSG: Label-Anonymized Distillation and SimilarGradient Substitution for
Label Privacy in Vertical Federated Learning.
.- Edge computing & Task scheduling.
.- CPRGO : Delay-Aware Task Scheduling Strategy for Edge-Cloud Continuum in
Multi-Hop Network Environments.
.-  Partial Pairwise Preference-Driven Task Allocation in Volunteer
Crowdsourcing.
.- A deep matrix completion method for recovering edge collaborative sensing
data in the Internet of Vehicles.
.- DCPS: A Novel Community-Interest-Aware Centralized Resource Scheduling
Method for Cooperative MEC Caching.
.- Adaptive Multi-Objective Task Scheduling for K3s-Enabled UAV Swarms.
.- Adaptive Multi-Resource Orchestration for Latency Critical Service
Function Chains in Mobile Edge Networks.
.- Joint Model Deployment and Task Offloading with Load Balancing for DNN
Inference in Vehicular Edge Computing.
.- Security and Blockchain applications.
.- MVTest: Automated Metamorphic Testing of Multi-View Perception Systems.
.- Cyber-Attack Detection in Federated Learning: A Bidirectionally Secure and
Verifiable Architecture.
.- GANBFL: A Reliable Incentive Mechanism for Federated Learning via GAN
Based Evaluation and Blockchain Integration.
.-  A Review of Hardware Accelerated Design and Optimization Techniques for
Reconfigurable Cryptosystems.
.- CLCBA: A Secure and Efficient Identity Authentication Scheme for
Cross-Chain Interoperability.
.- A Cross-Chain Key Agreement and Regulatory Governance Framework Based on
Peninsula Group
Permutation Rational Functions.
.- Anomaly Detection.
.- SkyPatrol: Aerial Peer Perspective Vision based Anomalous UAV
Recognition.
.- A Novel Dynamic Spatio-Temporal Collaborative Model for Multivariate Time
Series Anomaly Detection.
.- Topology-enhanced Graph Attention Network for Anomaly Detection in IIoT
Domain.
.- An Adversarial Detection and Defense Method based on Neural Discrete
Representation.
.- MemGT: Memory-augmented Graph Transformer based Unsupervised Model for
Collaborative Internet of Things Anomaly Detection.
.-  Multi-scale Timefrequency Collaborative Feature Learning for
Unsupervised Anomaly Detection in Fluctuating IoT Time Series.