Enhancement of the performance of MANET using machine learning approach based on SDNs

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dc.contributor.authorAbbood, Zainab Ali
dc.contributor.authorAtilla, Doğu Çağdaş
dc.contributor.authorAydın, Çağatay
dc.date.accessioned2023-01-24T09:36:58Z
dc.date.available2023-01-24T09:36:58Z
dc.date.issued2023en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractDeep learning (DL) is a subdivision of machine learning (ML) that employs numerous algorithms, each of which provides various explanations of the data it consumes; mobile ad-hoc networks (MANET) are growing in prominence. For reasons including node mobility, due to the potential wireless sensor network (WSN) to provide a small-cost solution to real-world contact challenges. But the lifespan in this network is restricted lifespan. Therefore, the wireless sensor network (WSN) is more vulnerable to battery consumption. On the other hand, routing packets in a Wireless Sensor Network (WSN) is a challenging task, according to the limited resources available on the nodes of these networks, especially their energy sources. The use of Machine Learning (ML) techniques in a Software-Defined Network (SDN) topology has shown good potential for solving such a complex task. However, existing techniques emphasize finding the shortest paths to deliver the packets, which can overload certain nodes in the network, depending on their positioning. In this study, a new method is proposed to extend the lifetime of the WSN by balancing the loading on the nodes, using a Deep Reinforcement Learning (DRL) approach. By emphasizing the lifetime of the network, the proposed method has been able to discover and use alternative routes to deliver the packets, avoiding the use of nodes with low energy. Hence, the average number of hops the packets travel through has been increased, but the time required for the first node to exhaust its energy has been significantly increased.en_US
dc.identifier.citationAbbood, Z. A., Atilla, D. Ç., Aydın, Ç. (2023). Enhancement of the performance of MANET using machine learning approach based on SDNs. Optik, 272, 170268.en_US
dc.identifier.issn0030-4026
dc.identifier.issn1618-1336
dc.identifier.scopus2-s2.0-85145605788
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3190
dc.identifier.volume272en_US
dc.identifier.wosWOS:000991395000008
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAbbood, Zainab Ali
dc.institutionauthorAtilla, Doğu Çağdaş
dc.language.isoen
dc.publisherElsevier GmbHen_US
dc.relation.ispartofOptik
dc.relation.isversionof10.1016/j.ijleo.2022.170268en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDLen_US
dc.subjectDRLen_US
dc.subjectMANETen_US
dc.subjectMLen_US
dc.subjectSDNen_US
dc.subjectWSNen_US
dc.titleEnhancement of the performance of MANET using machine learning approach based on SDNs
dc.typeArticle

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