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DC Field | Value | Language |
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dc.contributor.author | MENASRIA, AMAR | - |
dc.date.accessioned | 2022-10-18T08:36:00Z | - |
dc.date.available | 2022-10-18T08:36:00Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://dspace.univ-guelma.dz/jspui/handle/123456789/13487 | - |
dc.description.abstract | This work is part of an end of cycle master project aiming at a new model of Big Data storage in a Smart City environment. The objective is to propose a new distributed storage model for massive data coming from several sources in the Smart City. This model supports data storage at the device level, in order to reduce and eliminate several quantities such as: processing time, real response time, and latency. In case the memory of the device is full or saturated, the proposed model allows to exploit the network resources by ensuring the data distribution on other devices in order to avoid losing them. For the design, we opted for the CupCarbon simulator and the Python programming language. Keywords: Big Data, Smart city, Data distributed storage. | en_US |
dc.language.iso | fr | en_US |
dc.publisher | université de guelma | en_US |
dc.subject | méthode de stockage de données , Big Data , un environnement smart city | en_US |
dc.title | Vers une nouvelle méthode de stockage de données « Big Data » dans un environnement smart city | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Master |
Files in This Item:
File | Description | Size | Format | |
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MENASRIA_AMAR_F5.pdf | 2,66 MB | Adobe PDF | View/Open |
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