A Multiprotocol Controller Deployment in SDN-Based IoMT Architecture
dc.authorid | Çalhan, Ali/0000-0002-5798-3103 | |
dc.authorid | CİCİOĞLU, MURTAZA/0000-0002-5657-7402 | |
dc.authorwosid | Çalhan, Ali/H-1375-2014 | |
dc.authorwosid | CİCİOĞLU, MURTAZA/AAL-5004-2020 | |
dc.contributor.author | Cicioğlu, Murtaza | |
dc.contributor.author | Çalhan, Ali | |
dc.date.accessioned | 2023-07-26T11:58:01Z | |
dc.date.available | 2023-07-26T11:58:01Z | |
dc.date.issued | 2022 | |
dc.department | DÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.description.abstract | Internet of Medical Things (IoMT) as a next-generation network requires heterogeneous services, technologies, and equipment infrastructure management resulting in more complex systems. The software-defined networking (SDN) approach has emerged as a promising solution to reduce this complexity by proposing a vendor-independent structure that disaggregates the control and data planes. In this study, an architecture based on the SDN is proposed for such heterogeneous and complex IoMT networks. A new controller that supports different wireless communication protocols has been developed for the control plane. We propose machine learning (ML)-based load balancing and time-sensitive prioritization (MLA) algorithms for dense and dynamic networks. An SDN-based IoMT network that consists of IEEE 802.15.6, TDMA, and IEEE 802.11 protocols is analyzed in a simulation program simultaneously using various scenarios in terms of throughput, delay, packet loss ratio, bit error rate, and user density parameters. In addition, in this study, a new data set is created for load balancing. The performances of support vector machine (SVM), ensemble of decision trees, k-NN, and Naive Bayes ML algorithms are compared, and SVM gives the best result with 95.1% accuracy. | en_US |
dc.identifier.doi | 10.1109/JIOT.2022.3175669 | |
dc.identifier.endpage | 20840 | en_US |
dc.identifier.issn | 2327-4662 | |
dc.identifier.issue | 21 | en_US |
dc.identifier.startpage | 20833 | en_US |
dc.identifier.uri | https://doi.org/10.1109/JIOT.2022.3175669 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12684/13376 | |
dc.identifier.volume | 9 | en_US |
dc.identifier.wos | WOS:000871080800008 | en_US |
dc.identifier.wosquality | Q1 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.institutionauthor | Çalhan, Ali | |
dc.language.iso | en | en_US |
dc.publisher | Ieee-Inst Electrical Electronics Engineers Inc | en_US |
dc.relation.ispartof | Ieee Internet of Things Journal | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.snmz | $2023V1Guncelleme$ | en_US |
dc.subject | Protocols; Wireless Communication; Computer Architecture; Ieee 802; 15 Standard; Time Division Multiple Access; Standards; Internet Of Things; Machine Learning (Ml); Software-Defined Networking (Sdn); Wireless Sensor Networks | en_US |
dc.subject | Internet; Framework; Threats | en_US |
dc.title | A Multiprotocol Controller Deployment in SDN-Based IoMT Architecture | en_US |
dc.type | Article | en_US |