Scope and Topics
CCBD 2021 aims to be an annual event which gathers computer scientists, industrial engineers, and researchers to discuss and exchange experimental and theoretical results, novel designs, work-in-progress, experience, case studies, and trend-setting ideas in the areas of cloud computing and big data. With the aim of fostering collaboration and cross-fertilization of ideas from different communities.
CCBD also dedicates a large space to tutorials about a wide range of topics related to uncertainty management. Each tutorial provides a 45-minute survey of one of the research areas in the scope of the conference.
Topics of interest include (but are not limited to):
Architecture & Foundation of Cloud Computing and Big Data
- Infrastructure as a Service, Green Cloud Computing, Monitoring, Management and Maintenance of Cloud Platform
- Service-Oriented Architectures in cloud computing
- Software Defined Storage, Software Defined Network, and Software Defined Data Center
- Performance Improvement and Hardware Optimizations for Cloud Computing and Big Data
- Integrated Platform for Cloud Computing, Big Data, IoT and Social Networks
- Sensors, Devices and Embedded Systems Design in Cloud Computing
- Energy-efficient Cloud Computing for Big Data
- Open Platforms and System Architectures to Support Big Data
- Novel Theoretical and Computational Models for Big Data
- Best Practices for Migration to Cloud
Software Engineering, Tools & Services for Cloud Computing and Big Data
- Platform as a Service, DevOps, and API Management
- Software Engineering in Cloud Computing
- Job Scheduling, Load Balancing, Performance Evaluation & Improvement in Cloud Computing
- Novel Data Model and Databases for Emerging Hardware to Support Big Data
- Information Integration and Heterogeneous and Multi-structured Data Integration
- Novel Programming Model, Quality Measurement, Evaluation and Management
- Information lifecycle management for Cloud Computing and Big Data
- Business Process and Workflow Management in Cloud Services
- Innovative Cloud Applications, Novel Theoretical and Computational Models for Big Data
Knowledge Discovery & Data Engineering in Cloud Computing and Big Data
- Big Data Information Life Cycle Management
- Social Web Search and Mining
- Algorithms for Big Data Search
- Big Data Search Architectures, Scalability and Efficiency
- Big Data Analytic Algorithms, Knowledge Discovery & Data Engineering
- Visualization Analytics for Big Data
- Computational Modeling and Data Integration
- Large Scale Distributed, Knowledge Management
- Large-scale Recommendation Systems and Social Media Systems
- Cloud/Grid/Stream Data Mining - Big Velocity Data
- Multimedia and Multi-Structured Data - Big Variety Data
- Internet-Based Knowledge Engineering in Cloud Computing
Security, Privacy, Trust & Quality of Cloud Computing and Big Data
- Hardware/Software Reliability, Verification and Testing in Cloud Computing and Big Data
- Trusted Computing & Autonomic Computing in Cloud Computing and Big Data
- Fault Tolerance in Cloud Computing and Big Data
- Security and Privacy in Cloud Computing and Big Data
- Threat Detection using Big Data Analytics
- Privacy Preserving Big Data Collection/Analytics
- HCI Challenges for Big Data Security & Privacy
- Protection, Integrity and Privacy Standards and Policies for Big data
Business Models and Applications for Cloud Computing and Big Data
- Innovative Business Models and Applications of Cloud Computing and Big Data in Different Domains
- API Management, API Ecosystem, and API Economy
- Industrial IoT and Analytics