Logical data models for cloud computing architectures.

1. Logical data models for cloud
computing architectures (2012 IEEE)
Author: Augustine Samba, Kent State Uni
Presenter: Zafar Gilani

2. Cloud characteristics
• Five essential characteristics of cloud model:
– On demand self-service,
– Broad network access,
– Resource pooling,
– Rapid elasticity,
– Measured services.
• Three service models:
– SaaS
– PaaS
– IaaS

3. The challenge
• Developing efficient cloud architectures isn’t
trivial.
– A key challenge is to ensure an effective
foundation for evolving cloud services.

4. Focus of this paper
• The author analyses existing cloud
architectures and presents generic LDMs for
two such architectures:
– NIST cloud
– DMTF cloud
• Essentially a framework gathering a common
set of requirements.

5. Focus areas of various cloud
architectures

6. DMTF high level interaction
• Actors:
– Provider
– Developer
– Consumer

7. Service
provider can
An LDM for DMTF activate and
deactive
services for
each consumer.
Service provider
can customize
one or more
services for each
consumer.

8. NIST high level interaction
• Actors:
– Provider
– Consumer
– Broker
• An intermediary between Provider and Consumer.
– Carrier
• Handles hardware and network infrastructure.
– Auditor
• Performs assessment of services, operations and
performance.

9. Interacts with Cloud
Service broker acts
Management &
as an intermediary
Operations to provide
connectivity and
transport services to
An LDM for NIST to create bundle
services or enhance
existing ones.
the consumer.
Service auditor is an
intermediary that
assesses service
operation and
performance when
consumer launches a
service request.

10. Conclusion
• LDMs provide a foundation for developing
hybrid cloud architectures.
• Organizations can modify LDMs for their
specific needs and business requirements.
• Advantage?
– LDMs -> framework -> architecture(s).