"Cloud" is a common metaphor for an Internet accessible infrastructure (e.g. data storage and computing hardware) which is hidden from users. Cloud Computing makes data truly mobile and a user can simply access a chosen cloud with any internet accessible device. In Cloud Computing, IT-related capabilities are provided as services, accessible without requiring detailed knowledge of the underlying technology. Thus, many mature technologies are used as components in Cloud Computing, but still there are many unresolved and open problems. CloudCom-Asia 2016 aims to bring together researchers who work on cloud computing and related technologies.
Topics include but are not limited to:
1. Architecture
*Cloud Infrastructure as a Service
*Cloud Platform as a Service
*Cloud federation and hybrid cloud infrastructure
*Programming models and systems/tools
*Green data center
*Networking technologies for data center
*Cloud system design with FPGA, GPU, APU
*Monitoring, management and maintenance
*Economic and business models
*Dynamic resource provisioning
2. MapReduce
*Performance characterization and optimization
*MapReduce on multi-core, GPU
*MapReduce on hybrid distributed environments
*MapReduce on opportunistic / heterogeneous computing systems
*Extension of the MapReduce programming model
*Debugging and simulation of MapReduce systems
*Data-intensive applications using MapReduce
*Optimized storage for MapReduce applications
*Fault-tolerance & Self-* capabilities
3. Security and Privacy
*Accountability
*Audit in clouds
*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
4. Services and Applications
*Cloud Service Composition
*Query and discovery models for cloud services
*Trust and Security in cloud services
*Change management in cloud services
*Organization models of cloud services
*Innovative cloud applications and experiences
*Business process and workflow management
*Service-Oriented Architecture in clouds
5. Virtualization
*Server, storage, network virtualization
*Resource monitoring
*Virtual desktop
*Resilience, fault tolerance
*Modeling and performance evaluation
*Security aspects
*Enabling disaster recovery, job migration
*Energy efficient issues
6. HPC on Cloud
*Load balancing for HPC clouds
*Middleware framework for HPC clouds
*Scalable scheduling for HPC clouds
*HPC as a Service
*Performance Modeling and Management
*Programming models for HPC clouds
*HPC cloud applications
*Optimal cloud deployment for HPC
7. Big Data:
*Machine learning
*Data mining
*Approximate and scalable statistical methods
*Graph algorithms
*Querying and search
*Data Lifecycle Management for Big Data (sources, cleansing, federation, preservation, privacy, etc.)
*Frameworks, tools and their composition
*Storage and analytic architectures
*Performance and debugging
*Hardware optimizations for Big Data (multi-core, GPU, networking, etc.)
*Data Flow management and scheduling
