Información de la conferencia

CCBD 2019: International Conference on Cloud Computing and Big Data

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Día de Entrega:
2018-10-30 Extended
Fecha de Notificación:
Fecha de conferencia:
2019-01-03
Ubicación:
Sanya, China
Ediciones:
9
Vistas: 26431   Seguidores: 13   Asistentes: 4

Solicitud de Artículos

CCBD 2019 (International Conference on Cloud Computing and Big Data) is an academic conference held in Sanya, China on 2019-01-03. The paper submission deadline is 2018-10-30 (extended).

The International Conference on Cloud Computing and Big Data (CCBD 2019) will be held from January 3 to 5, 2019 in Sanya, China. You are invited to submit papers and participate in our academic exchange. Topics: The conference is soliciting state-of-the-art research papers in the following areas of interest: Cloud computing Cloud Solution Design Patterns Cloud Application Architectures Cloud Middleware Frameworks Cloud Quality and Performance Cloud Optimization and Automation Cloud Resource Virtualization and Composition Cloud Management and Operations Cloud Resource Virtualization and Composition Intelligent Data Processing Semantic web technologies Cloud Architecture Cloud Infrastructure as a Service Cloud Platform as a Service Cloud system design Cloud federation and hybrid cloud infrastructure Programming models and systems Networking technologies for data center Security and Privacy in Cloud Authentication and authorization Cryptographic primitives Reliability and availability Trust and credential management Usability and security Security and privacy in clouds Legacy systems migration Cloud Integrity and Binding Issues Big Data Big Data Analysis Processing Big Data Analysis Analytics and Metrics Big Data Analysis Architectures Big Data Analysis Encryption Big Data Analysis Management Big Data Analysis Search and Mining Machine learning Data mining Approximate and scalable statistical methods Querying and search Data Lifecycle Management for Big Data Storage and analytic architectures Performance and debugging Hardware optimizations for Big Data Data Flow management and scheduling
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