A Backup Model: (QoS Guaranteed and Less Consumed Energy) for Cloud SDN Using Neural Networks

Ammar Alsous (), Jorge Marx Gómez and Manuel Mora
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Ammar Alsous: Carl von Ossietzky University of Oldenburg
Jorge Marx Gómez: Carl von Ossietzky University of Oldenburg
Manuel Mora: Autonomous University of Aguascalientes

A chapter in Resilience, Entrepreneurship and ICT, 2021, pp 355-387 from Springer

Abstract: Abstract Cloud services include significant benefits for the provider and the customer. It depends on the resource sharing concept, which is important to increase the resources utilization and to reduce the customer’s costs. Software Defined Networking (SDN) is a new networking paradigm. It is used to virtualize a network and offer it to several users as several networks. SDN paradigm supports “Green Networking” by reducing and reducing CO2 emissions. According to the performed literature review, cloud backup services (using SDN) still need enhancements regarding preserving Quality of Service (QoS) during the operation. This research focuses on the problem of performing a backup between data centers and guaranteeing the QoS at the same time. The proposed solution depends on finding a route between the source and destination nodes that satisfies the customer’s QoS criteria. It combined the concepts of SDN, cloud services, and guaranteed QoS together. AI techniques (neural networks) were used to check backup paths. With a comparison between 20 AI techniques, the research results were very promising. They showed that the results’ accuracy is high and neural networks are a very good option to adopt.

Keywords: Software defined networking; Green networking; Quality of service; Backup; Cloud services (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:csrchp:978-3-030-78941-1_17

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DOI: 10.1007/978-3-030-78941-1_17

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