An inexpensively elastic resource allocation model for platform as a service cloud computing
Citation:
Xiaobin Xiao, 'An inexpensively elastic resource allocation model for platform as a service cloud computing', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2015, pp 171Download Item:
Xiao TCD THESIS 11104 An inexpensively.pdf (PDF) 61.23Mb
Abstract:
With the growth in cloud computing there is additional complexity introduced in cloud
systems and therefore there is a need for more efficient resource allocation. Autonomic
computing is a promising approach for resource allocation in cloud computing and this
approach advocates for self-managing ability whereby autonomic systems can allocate
resources for their own needs without intervention from humans. In the Platform-asa-
Service (PaaS) model, the platform provider requests for resources such as CPU and
RAM from the infrastructure provider and ensures the end client who has requested for
platform resources is allocated sufficient resources to meet their requirements. In the
PaaS model, platform providers suffer volatile resource demands and high provisioning
costs due to resource prediction errors and penalties that arise due to SLA violations.
Author: Xiao, Xiaobin
Advisor:
Barrett, StephenQualification name:
Doctor of Philosophy (Ph.D.)Publisher:
Trinity College (Dublin, Ireland). School of Computer Science & StatisticsNote:
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