Prospective authors are invited to submit high-quality original technical papers for presentation at the conference and publication in the conference proceedings. The topics are not limited to those as below:

Track 1: Cloud Computing Fundamentals, Architecture, and Distributed Ecosystems

Emerging cloud models (public, private, hybrid clouds)
Cloud service architectures (IaaS, PaaS, SaaS)
Cloud deployment strategies
Cloud computing and semantic web technologies
Cloud Computing Architecture and Systems
Cloud Computing Models, Simulations, Designs, and Paradigms
Cloud Computing Technologies, Services and Applications
Cloud Economics
Cloud Management and Operations
Cloud Middleware Frameworks
Cloud Optimization and Automation
Cloud Quality and Performance
Cloud Solution Design Patterns

Track 2: Security and Privacy in Cloud and Big Data

Security and privacy in cloud computing
Security challenges in cloud-based IoT applications
Data governance and compliance in the cloud
Security and privacy for big data
Privacy Preserving Big Data Analytics
Blockchain based lightweight data structures for IoT data
Collaborative Threat Detection using Big Data Analysis Analytics

Track 3: Big Data Technologies, Frameworks, and Intelligent Systems

Big data frameworks and tools (Hadoop, Spark, etc.)
Algorithms and Systems for Big Data Analysis Search
Big Data Storage, Indexing, Searching and Querying
Techniques, models and algorithms for big data
Tools and systems for big data
Intelligent Data Processing
Hardware/software infrastructure for big data
Big Data Open Platforms
Experience with Big Data Project Deployments
Big Data Toolkits

Track 4: Data Analytics and Machine Learning

Machine learning and artificial intelligence in big data
Data mining techniques and applications
Big Data Analysis Analytics and Metrics
Machine learning and AI for big data
City-scale Data Mining and Machine Learning
Visualization Analytics for Big Data
Data mining, graph mining and data science
Foundational Models for Big Data
Issues, problems and opportunities in Big Data

Track 5: IoT, Edge Computing, and Cloud Integration

IoT architecture and cloud integration
Data management and analytics in IoT environments
Edge vs. cloud computing paradigms
Data processing and analytics at the edge
Applications and case studies of edge computing
Challenges and solutions in edge computing deployment
Social impact and sustainability in cloud and big data applications
Innovative use cases leveraging cloud and big data technologies

Track 6: Application of Cloud and Big Data in Various Industries

Industry-specific applications (healthcare, finance, smart cities, etc.)
Big Data for Vertical Industries (including Government, Healthcare, and Environment)
Big Data Analysis for Business Model Innovation
Big Data in Government Management Models and Practices
Real-life Case Studies of Value Creation through Big Data Analytics

Track 7: Future Trends and Challenges in Cloud and Big Data

Emerging trends in cloud computing and big data
Ethical considerations and societal impacts
Regulatory changes affecting cloud and big data
Research challenges and future directions
Big Data Analysis Economics
Big Data for Business Model Innovation
SME-centric Big Data Analytics

Track 8: Cloud Storage and Data Management

Data storage and retrieval in cloud environments
Data integration and interoperability
Cloud-based database management systems
Data Quality and Provenance Control
Framework for Data Understanding and Quality
New Data Standards and Programming Models
Representation Formats for Multimedia Big Data