Toward a Unified Ontology of Cloud Computing Lamia Youseff University of California, Santa Barbara Maria Butrico, Dilma Da Silva IBM T.J. Watson Research Center 1
In the Cloud Several Public Cloud Computing Offerings * Nimbus @ University of Chicago * Stratus @ University of Florida 2
In the Cloud Hardware as a service (HAAS) Service Oriented Architectures (SOA) Hardware-assisted Virtualization Paravirtualization Peer-to-Peer Computing Software as a service (SAAS) Distributed and Grid Computing Map-Reduce Data as a service (DAAS) 3
Goal of our study Understanding the cloud computing landscape Dissection of cloud computing field Five main layers Depict inter-relationship between the layers Depict inter-dependency on preceding technologies Our Contribution 4
Outline Introduction: In the cloud Goal of our study Motivation Classification Methodology Cloud Ontology Research Opportunities and Discussions Questions 5
Classification Methodology Principle of Composibility (SOA) Stack of layers One Cloud layer is higher in stack If its services can be composed of the services of underlying layers. Cloud services belong to same layer if they have equivalent levels of abstraction Evident by their targeted users 6
Proposed Cloud Ontology 7
Layer 1: Cloud Application Software as a Service (SaaS) Favorable benefits to its users Favorable benefits to its developers Construction and Composibility of SaaS. Limitations Availability of Applications Security of Data Legacy Application Migration Disaster recovery Reliable SLA. 8
Layer 2: Cloud S/W Environment Platform as a service (PaaS) Provides APIs and runtime environment Favorable benefits to users; i.e developers Favorable benefits to the provider Example: open-source map-reduce Hadoop 9
Layer 3: Cloud S/W Infrastructure Provides fundamental S/W resources Composed of three constituents Computational Resources Infrastructure as a Service (IaaS) Enabled by Virtualization Limitations in Performance Isolation Data Storage (DaaS) High Availability, reliability, performance, replication, data consistency. Conflicting goals: Consistency vs availability Different Approaches Communications (CaaS) Provides network communications with QoS Research Opportunities: Traffic Isolation, Guaranteed message-delay, Dynamic provision of overlays 10
Layer 4: Software Kernel Basic software management of Physical servers. e.g. OS Kernel, hypervisor, VMM, clustering middleware Grid and Cluster Computing e.g. Globus and Condor Further integration of Grid Research to Cloud computing research Micro-economics grid models For pricing, metering and supply demand equilibrium. Cloud Utility computing 11
Layer 5: Firmware and Hardware Hardware as a Service (HaaS) Actual Physical Hardware Favorable benefits to users, i.e. Enterprise users Favorable benefits to providers Challenges : Scalable, easy and fast bare-hardware provisioning Remote scriptable boot-loaders. Example: IBM Kittyhawk, and IBM-Morgan Stanley 04 lease 12
Proposed Cloud Ontology Software as a Service (SaaS) Platform as a Service (PaaS) Infrastructure as a Service (IaaS) Data Storage as a Service (DaaS) Communications as a Service (CaaS) Hardware as a Service (HHaaS) 13
Discussion Business incentive for cloud computing Pricing models Tiered-pricing Per-unit pricing Subscription based pricing Security and Privacy concerns in the cloud Monitoring for cloud systems Clouds for HPC systems 14
Questions Lamia Youseff lyouseff@cs.ucsb.edu http://www.cs.ucsb.edu/~lyouseff 15
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Motivation Assist scientific community to expedite contribution to an emerging field Defining Inter-relationship enables enhancing features. Example: supporting High Availability and Resilience Example: Allowing inter-operability between cloud offerings Defining Interdependency on preceding technologies enables identifying limitations and optimization opportunities Simplify the Educational Efforts 17