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Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network

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Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network

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dc.contributor.author Rehman, Amjad es_ES
dc.contributor.author Haseeb, Khalid es_ES
dc.contributor.author Fati, Suliman Mohamed es_ES
dc.contributor.author Lloret, Jaime es_ES
dc.contributor.author Peñalver Herrero, Mª Lourdes es_ES
dc.date.accessioned 2022-04-28T18:04:55Z
dc.date.available 2022-04-28T18:04:55Z
dc.date.issued 2021-11 es_ES
dc.identifier.uri http://hdl.handle.net/10251/182271
dc.description.abstract [EN] Nowadays, the Internet of Things (IoT) performs robust services for real-time applications in monitoring communication systems and generating meaningful information. The ZigBee devices offer low latency and manageable costs for wireless communication and support the process of physical data collection. Some biosensing systems comprise IoT-based ZigBee devices to monitor patient healthcare attributes and alert healthcare professionals for needed action. However, most of them still face unstable and frequent data interruption issues due to transmission service intrusions. Moreover, the medical data is publicly available using cloud services, and communicated through the smart devices to specialists for evaluation and disease diagnosis. Therefore, the applicable security analysis is another key factor for any medical system. This work proposed an approach for reliable network supervision with the internet of secured medical things using ZigBee networks for a smart healthcare system (RNM-SC). It aims to improve data systems with manageable congestion through load-balanced devices. Moreover, it also increases security performance in the presence of anomalies and offers data routing using the bidirectional heuristics technique. In addition, it deals with more realistic algorithm to associate only authorized devices and avoid the chances of compromising data. In the end, the communication between cloud and network applications is also protected from hostile actions, and only certified end-users can access the data. The proposed approach was tested and analyzed in Network Simulator (NS-3), and, compared to existing solutions, demonstrated significant and reliable performance improvements in terms of network throughput by 12%, energy consumption by 17%, packet drop ratio by 37%, end-to-end delay by 18%, routing complexity by 37%, and tampered packets by 37%. es_ES
dc.description.sponsorship This research is supported by Artificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University, Riyadh, Saudi Arabia. Authors are thankful for the support. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Applied Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Reliable data transfer es_ES
dc.subject Internet of secured things es_ES
dc.subject Public health es_ES
dc.subject Mobility es_ES
dc.subject ZigBee devices es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/app11219947 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Rehman, A.; Haseeb, K.; Fati, SM.; Lloret, J.; Peñalver Herrero, ML. (2021). Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network. Applied Sciences. 11(21):1-16. https://doi.org/10.3390/app11219947 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/app11219947 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 21 es_ES
dc.identifier.eissn 2076-3417 es_ES
dc.relation.pasarela S\450792 es_ES
dc.contributor.funder Artificial Intelligence and Data Analytics Lab, Prince Sultan University es_ES


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