Implementation of the Flexible "Private - Public" Cloud Solution based on OpenStack

Authors

  • M. Elmahouti Laboratory ISERG Abdelmalek Essaadi University, Tétouan, Morocco
  • O. Achandair Abdelmalek Essaadi University, Tétouan, Morocco
  • Samira Khoulji
  • M.L. Kerkeb Abdelmalek Essaadi University, Tétouan, Morocco

DOI:

https://doi.org/10.14738/tmlai.54.3334

Keywords:

Cloud computing, Private cloud, Public cloud Information resources, Information security, OpenStack

Abstract

Cloud computing is a model that facilitates access to and manipulation of resources on demand. It is a technology that is unique today to meet the needs and demands of customers by guaranteeing a high quality of service rendered. This new model provides convenience to reorganize the current revolt in the information technology industry by ensuring cost effective and less costly solutions to meet the constraints of technical capabilities and their extension.This article will present the technical implementation of a flexible "private - public" cloud computing, based on the Openstack solution, to ensure the business needs in terms of performance, and a response time of treatments tailored to customer demand with a Availability.This approach, followed by a "private-public" flexible cloud, will be able to communicate two clouds, the Cloud A, which includes the entire physical infrastructure of the company, while cloud B will be provided by a service provider that does not Will be called once the configurable load threshold is exceeded on the cloud A, and as soon as the resources on the private cloud A are released, the instances migrated to the Cloud B will be again remigrated to the Cloud A to minimize even the times Allocation.

 


References

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Published

2017-09-01

How to Cite

Elmahouti, M., Achandair, O., Khoulji, S., & Kerkeb, M. (2017). Implementation of the Flexible "Private - Public" Cloud Solution based on OpenStack. Transactions on Engineering and Computing Sciences, 5(4). https://doi.org/10.14738/tmlai.54.3334

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems

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