Call for Paper

Scope and Topics

CCBD 2020 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