The 1st IEEE International Conference on Hot Information-Centric Networking (HotICN 2018)

(1) Track1: ICN

ICN architecture and fundamentals

• Routing and forwarding
• Congestion Control
• Hybrid networks, such as Integration ICN with SDN or IPv6 or DNS
• Caching policy and management
• Smart ICN (AI in ICN)      
• Data Center/High speed ICN
• Prototype equipments for ICN Deployement

ICN mobility

• • Producer/Consumer mobility, hand-over management
  • 5G ICN
  • Vehicle Networks or dynamic networking

ICN in IoT

• • Fog Computing or Edge networks
  • IoT-specific security

Security Issues in ICN

• • Privacy issues
  • Caching related security problems
  • Access Control
  • Trust management

ICN performane and evaluation

• Network Qos、Reliabiltiy
• System performance and Application oriented performance
• Green ICN (energy saving or cost reducing)
• Monitoring and debugging
• Testbed or benchmarking

ICN-inspired applications and systems

• ICN advantages in Ad hoc network
• Tools, add-ons and thinner ICN systems
• Content distribution and P2P
• Distributed ICN algorithms and systems
• Cloud-based services, Database, Big data
• Streaming application and VR/AR
• Implementation challenges and experiences

ICN analysis and theory

• Simulation or real system analysis (eg. Scalability or bottleneck)
• Fundemantal control and optimization theories
• Traffic Engineering
• Methodology and metrics

(2) Track2: Blockchain

1. Blockchain Technologies and Systems.
2. Distributed Consensus Algorithms.
3. Digital currency or Cryptocurrencies technologies
4. Security, privacy and trust issues with blockchain schemes.
5. Performance and scalability optimization of blockchain system.
6. Testing, simulation, and modeling.
7. Smart contracts and distributed ledger applications.
8. Innovative applications with blockchain technique (eg. IoT, Fintech).

(3) Track3: Knowledge graph

Information Extraction

• Knowledge extraction
• Named entity recognition, entity disambiguation and linking
• Relationship extraction, event extraction
• Semantic similarity / Metric learning

Information Retrieval

• Algorithm, models and theory of IR
• Text filtering, mining, classification and clustering, community mining
• Content Recommendation, Analysis and Classification
• Topic detection and summarization
• Interactive research, UI and visualization

Knowledge Representation

• Knowledge representation learning
• Knowledge graph embedding, modeling
• Knowledge graph mapping, merging, reuse, and alignment
• Quality issues, assessment metrics and measures in knowledge graphs

Knowledge Graph Based Application

• Machine translation
• Question Answering, Dialogue and interactive systems
• Use cases in natural language processing, knowledge management, data integration, data publishing, smart data access and analytics
• Specific applications in various verticals: medicine, business, industry and cultural heritage