Availability modeling for multi-tier cloud environment

Nalinipriya, G.; Maheswari, K; Balamurugan, B.; Kotteswari, K.; Sangaiah, Arun Kumar

doi:10.1080/10798587.2016.1220122

Cited by 7 publications

(2 citation statements)

References 19 publications

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“…Although 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. Reliability is the assertion that cloud provisions are free from software faults, hardware faults, and other faults that break down the system's efficiency.…”

Section: Introductionmentioning

confidence: 99%

Spectral Expansion Method for Cloud Reliability Analysis

Kotteswari¹,

Bharathi²

2019

Journal of Computer Networks and Communications

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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.

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Section: Introductionmentioning

confidence: 99%

Spectral Expansion Method for Cloud Reliability Analysis

Kotteswari¹,

Bharathi²

2019

Journal of Computer Networks and Communications

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“…In addition, there has been continuing work in the area of reliability and availability modeling and evaluation. ()…”

Section: Introductionmentioning

confidence: 99%

ReliaCloud‐NS: A scalable web‐based simulation platform for evaluating the reliability of cloud computing systems

et al. 2017

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This paper discusses the implementation, architecture, and use of a graphical web-based application called ReliaCloud-NS that allows users to (1) evaluate the reliability of a cloud computing system (CCS) and (2) design a CCS to a specified reliability level for both public and private clouds. The software was designed with a RESTful application programming interface for performing nonsequential Monte Carlo simulations to perform reliability evaluations of a CCS. Simulation results are stored and presented to the user in the form of interactive charts and graphs from within a web browser. The software contains multiple types of CCS components, simulations, and virtual machine allocation schemes. ReliaCloud-NS also contains a novel feature that evaluates CCS reliability across a range of varying virtual machine allocations and establishes and graphs a CCS reliability curve. This paper discusses the software architecture, the interactive web-based interface, and the different types of simulations available in ReliaCloud-NS and presents an overview of the results generated from a simulation.

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Spectral Expansion Method for Cloud Reliability Analysis

Kotteswari

Bharathi²

2019

2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)

Self Cite

View full text Add to dashboard Cite

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 ings (IoT). e 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. ese 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. e spectral expansion method (SPM) is a huge technique useful in reliability and performance modelling of the computing system. is approach solves the Markov model of cloud service providers (CSP) to predict the reliability. e SPM is better compared to matrix-geometric methods.

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Availability modeling for multi-tier cloud environment

Cited by 7 publications

References 19 publications

Spectral Expansion Method for Cloud Reliability Analysis

Spectral Expansion Method for Cloud Reliability Analysis

ReliaCloud‐NS: A scalable web‐based simulation platform for evaluating the reliability of cloud computing systems

Spectral Expansion Method for Cloud Reliability Analysis

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