(Include but not limited to)
Track 1: Edge Computing
Edge computing architecture and design of edge intelligent systems
Cloud-edge-end collaborative computing architecture and resource orchestration
Edge resource scheduling, task offloading and load balancing
Edge caching, content delivery network and real-time stream processing
Edge security, trusted execution environment and privacy protection
Edge AI model lightweight deployment and inference optimization
Intelligent perception algorithms of edge computing
Deep learning applications of edge computing
Adaptive learning technology of edge computing
Data mining of edge computing
Enhanced learning of edge computing
Integration methods of edge intelligent algorithms
Prediction models of edge computing
Automatic decision-making of edge computing
Optimization algorithms of edge computing
5G/6G edge networks and communication protocol optimization
Applications of edge computing in industrial Internet of Things, smart cities, autonomous driving and other scenarios
Track 2: Big Data Processing
Basic models of big data
Data science
Big data search
Memory system Deep Learning
High-performance computing technology
Network infrastructure
Multi-core computing
Big data application
Fault tolerance and reliability
Big data system
Big data privacy and security
Big data archiving and preservation
Data analysis and data mining
Intelligent information processing
Multivariate heterogeneous data fusion
Big data analysis and intelligent recommendation
Track 3: Distributed systems
Distributed storage systems, key-value storage and new storage media
Distributed scheduling, load balancing and resource management
Distributed system fault tolerance, fault recovery and observability
Distributed machine learning and federated learning systems
Microservice architecture, container orchestration and serverless computing
Distributed system performance modeling and evaluation
AI-driven distributed system optimization (AI for Systems)
Intelligent operation and resource scheduling enabled by large language models
Application of blockchain and distributed ledger technology in data management
Cross-exploration of quantum computing and distributed systems
Federated edge learning and privacy-preserving distributed intelligence