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The International Conference on Intelligent and Cloud Computing (ICICC-2019) aims at the crossroads between scientists, researchers, practitioners and students from diverse domains in cloud computing research. The conference aims at attracting contributions of system and network design that can support existing and future applications and services. In recent years, intelligent and cloud computing attracted significant attention both in research and industry. This approach corresponds to natural human vision and is the best way to represent, generate and implement various contemporary achievements. The International Conference on Intelligent and Cloud Computing (ICICC-2019) will provide a forum that will bring together researchers, academia and practitioners from industry to meet and exchange their ideas and recent research achievements in all aspects of intellegent and Cloud Computing, together with their applications in the contemporary world. The scope of this conference has been kept wide and following are the topics covered (But not limited to):
Cloud computing system and network design
Cloud network protocol design and management
Optimization for cloud computing, networking, and applications
Green cloud system design
Cloud storage design and networking
Cloud system and storage security
Cloud network virtualization techniques
Modeling for cloud system, network and storage
Performance analysis for cloud system, network and storage
Big data storage and networking in the Clouds
Intra-cloud computing and networking
Mobile Cloud system design
Cloud media and storage design
Real-time resource reporting and monitoring for cloud management
Cloud system interoperability
Cloud data center design
Utility computing solutions in Cloud systems
Cloud forensics
Networking for cloud computing
Machine learning, data mining for cloud computing
Edge, fog, and mobile edge computing
Security, privacy, trust for cloud computing
Machine learning for cloud resource management
Machine learning for traffic engineering and congestion control
Machine learning for network measurement
Data-driven methodology and architecture
Networking for machine learning systems
Resource management and device placement for machine learning systems
Measurement and diagnosis for machine learning systems
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