THESIS
2015
xxii, 224 pages : illustrations ; 30 cm
Abstract
Cloud computing systems are inherently large scale, highly distributed, virtualized,
and operate in automated shared environments. Thus, performance and dependability
of cloud is affected by a large number of parameters. Further, cloud resources need to
be agile and reconfigurable in order to respond quickly to ever changing application demands
and service requirements. Significant research work has been done on designing
cloud computing infrastructures in order to boost the performance and dependability
of cloud computing systems.
In this thesis, we develop various techniques for service-oriented performance and
dependability evaluation. We start with a discussion on the modeling of evaluation
techniques and metrics in different fashions for one of the service-oriented environ...[
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Cloud computing systems are inherently large scale, highly distributed, virtualized,
and operate in automated shared environments. Thus, performance and dependability
of cloud is affected by a large number of parameters. Further, cloud resources need to
be agile and reconfigurable in order to respond quickly to ever changing application demands
and service requirements. Significant research work has been done on designing
cloud computing infrastructures in order to boost the performance and dependability
of cloud computing systems.
In this thesis, we develop various techniques for service-oriented performance and
dependability evaluation. We start with a discussion on the modeling of evaluation
techniques and metrics in different fashions for one of the service-oriented environments,
the telecommunication systems. In the analysis, we focus on highlighting the factors
that affect the performance and dependability of service. Specifically, we perform the
service-oriented dependability analysis using an service (un)reliability measure called
Defects Per Million (DPM) than the traditional system-oriented dependability analysis
which do not fully reflect the impact of system failure-recovery behavior in service-oriented
environments. Thereafter, we extend the aforementioned analysis to cloud
computing systems.
A good understanding of state-of-the-art cloud infrastructures would help finding all
potential system vulnerabilities as well as enable the cloud architectures providing better
cloud service. Accordingly, we present an analysis using a framework to illuminate
areas for concern and identify areas for potential cloud service and security enhancements.
Further, existing cloud computing systems consume a vast amount of energy
and have a substantial impact on the environment, consequently we present suitable
techniques for reducing energy consumption as well as for reducing the environmental
impact while meeting the Service Level Agreements (SLAs). We show the evaluation
of trade-offs amongst performance, dependability, and
1sustainability as well.
1In this thesis, sustainability is addressed by optimizing energy consumption in cloud data centers.
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