The increasing popularity of cloud computing and the increasing market competition among the cloud computing service providers creates an urgent need to have an easy and effective performance analysis method suited to the large IaaS cloud computing environment. This would consist of millions of physical and virtual computers, so that the cloud computing service providers can most efficiently provision and configure their computation resources to achieve the optimized utilization of their computation resources.
Theoretically, the following 3 approaches can be used to conduct performance analysis to any type of target system:
Experiment-based performance analysis
Discrete event-simulation-based performance analysis
Stochastic model-based performance analysis
Because of the very large scale of cloud computing environment, both experiment-based performance analysis and discrete event simulation are not cost-effective due to the number of computer resource and the time required to run the experiments. Therefore, from the low-cost point view, the stochastic model-based performance analysis becomes the only natural choice.
However, the nature of the large scale of the cloud computing has also posed the challenge of building a practical and scalable stochastic model. If applying the conventional stochastic model building principle such as capturing as many details as possible of the cloud computing environment into one-level monolithic model, the resulted state space of the Markov model will become very large. This may make the generation and solution of such a model a prohibitively difficult task.
Sakr and Gaber have proposed a relatively simple but also scalable stochastic model for analyzing performance of IaaS cloud computing environment based on the interactions among several submodels such that the overall solution composed by the iteration over individual sub-model solutions (2014).
Create a study report focusing on the following aspects:
Identify the main concept of the stochastic model proposed by Sakr and Gaber.
Discuss why the three-pool cloud architecture-based stochastic model proposed in Sakr and Gaber can be scalable and practical to do performance analysis on IaaS cloud computing environment.
Discuss the main limitation of the three-pool cloud architecture model, and how to remove the limitation.
Discuss the potential applications that can be developed based on this type of performance analysis approach.
You need to present the justification or rationale on your point of view. You should use examples to illustrate your point of view. Find at least 2 references from the Library and the Internet based on your research interests. You will need at least 3 references for this report.
Reference
Sakr, S., & Gaber, M. (Eds.). (2014). Large scale and big data: Processing and management. CRC Press.