Abstract
Cloud computing is a computing hypothesis, where a huge group of systems is linked together in private, public, or hybrid network, to offer dynamically amendable infrastructure for data storage, file storage, and application. With this emerging technology, application hosting, delivery, content storage, and reduced computation cost are achieved, and it acts as an essential module for the backbone of the Internet of Things (IoT). The efficiency of cloud service providers (CSP) could be improved by considering significant factors such as availability, reliability, usability, security, responsiveness, and elasticity. Assessment of these factors leads to efficiency in designing a scheduler for CSP. These metrics also improved the quality of service (QoS) in the cloud. Many existing models and approaches evaluate these metrics. But these existing approaches do not offer efficient outcome. In this paper, a prominent performance model named the “spectral expansion method (SPM)” evaluates cloud reliability. The spectral expansion method (SPM) is a huge technique useful in reliability and performance modelling of the computing system. This approach solves the Markov model of cloud service providers (CSP) to predict the reliability. The SPM is better compared to matrix-geometric methods.
Highlights
Cloud computing is a computing model for enabling expedient, on-demand network service to a pool of computing resources such as servers, storage, networks, services, and applications that can be promptly planned and released with minimum executive effort or service provider interface
One-tier, two-tier, 3-tier, to N-tier models are available in the cloud to provide n no. of services based on the tier type
To maintain the capacity of the model, the reliability evaluation is necessary for this multitier cloud system
Summary
Cloud computing is a computing model for enabling expedient, on-demand network service to a pool of computing resources such as servers, storage, networks, services, and applications that can be promptly planned and released with minimum executive effort or service provider interface. Various studies have proposed approaches recently on maintaining availability and balancing power performance [7,8,9,10], no one considered reliability, another major factor of cloud service. The high-level performance modelling called the spectral expansion method is proposed to estimate the reliability of the cloud computing environment. E remaining section of the paper is described as follows: Section 2 discusses existing studies; Section 3 explains the background of multitier cloud environment; Section 4 describes the spectral expansion model and algorithm; Section 5 illustrates numerical analysis and comparison between other models; and, Section 6 concludes with a conclusion and future work. E spectral expansion method is applied for the performance and dependability analysis of the computing system. The SPM is applied to predict the reliability of cloud-based service
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