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Link to original content: https://doi.org/10.1007/978-3-319-91192-2_25
Improved Adaptive Fault Tolerance Model for Increasing Reliability in Cloud Computing Using Event-B | SpringerLink
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Improved Adaptive Fault Tolerance Model for Increasing Reliability in Cloud Computing Using Event-B

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Cybernetics and Algorithms in Intelligent Systems (CSOC2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 765))

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Abstract

Cloud computing provide services to many users at the same time by providing virtual resources via internet, General example of cloud services is Google apps, provided by Google. In most of cloud applications, processing is done on remote cloud computing nodes. So, there are more chances of errors, due to the undetermined latency and lose control over remote nodes, so it is very important apply the techniques for fault tolerance in cloud computing.

In this paper, a fault tolerance in real time cloud computing is proposed. In our model, the system tolerates the faults and makes the decision on the basis of reliability of the processing nodes.

And we will present an event-B as formal method that can be used in the development of reactive distributed systems and we propose using the Rodin modeling tool for Event-B that integrates modeling and proving.

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References

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Acknowledgement

This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme project No. LO1303 (MSMT-7778/2014) and by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089. Also supported by grant No. IGA/CebiaTech/2017/007 from IGA (Internal Grant Agency) of Tomas Bata University in Zlin.

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Correspondence to Roman Jasek .

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Ali, A.A., Jasek, R., Krayem, S., Chramcov, B., Zacek, P. (2019). Improved Adaptive Fault Tolerance Model for Increasing Reliability in Cloud Computing Using Event-B. In: Silhavy, R. (eds) Cybernetics and Algorithms in Intelligent Systems . CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 765. Springer, Cham. https://doi.org/10.1007/978-3-319-91192-2_25

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