Using Multiple RPL Instances to Enhance the Performance of New 6G and Internet of Everything (6G/IoE)-Based Healthcare Monitoring Systems

Mardini, Wail; Aljawarneh, Shadi; Al-Abdi, Amnah

doi:10.1007/s11036-020-01662-9

Cited by 23 publications

(5 citation statements)

References 43 publications

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“…These include remote real‐time health monitoring, telemedicine, home, and elderly healthcare and the detection and prevention of chronic diseases. Wearables, bio‐integrated devices, and bio‐nano intelligent systems are being developed with rapid speed to facilitate real‐time healthcare services (Barakat et al, 2021; Bhat & Alqahtani, 2021; Hewa et al, 2020; Mardini et al, 2021; Mucchi et al, 2020; Nayak & Patgiri, 2020; Padhi & Charrua‐Santos, 2021a). These IoT devices such as the ones described in Nasrollahzadeh et al (2020) and Strobel and Mittnacht (2021) help to sense biological and chemical changes around a patient and send the collated data to edge or fog data center environments for further processing (Al‐Turjman, 2020).…”

Section: G Enabled Iot Environmentsmentioning

confidence: 99%

Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks

Akinbi

2023

WIREs Forensic Science

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The development of sixth‐generation (6G) wireless communication technology is expected to provide super high‐speed data transmission, and advanced network performance than the current fifth‐generation (5G) and be fully functional by the 2030s. This development will have a significant impact and add improvements to digital extended reality (XR), autonomous systems, vehicular ad hoc networks (VANETs), artificial intelligence (AI), underwater communications, blockchain technology, pervasive biomedical informatics and smart cities built on the digital infrastructure backbone of the Internet of Things (IoT). The ubiquitous nature of this large‐scale 6G‐enabled IoT that offers faster connectivity capabilities and integrates both terrestrial and non‐terrestrial networks will not only create new data security and privacy issues but also provide a treasure trove of digital evidence useful for digital forensic examiners investigating security incidents and cybercrime. However, for digital forensic examiners, evidence collection, preservation and analysis will become a priority in the successful deployment of 6G IoT networks. In this study, we define key applications of 6G network technology to the Internet of Things and its existing architectures. The survey introduces potential digital forensic challenges and related issues affecting digital forensic investigations specific to 6G IoT networks. Finally, we highlight and discuss forensic readiness and future research directions for identified challenges within the 6G IoT network environments.This article is categorized under: Digital and Multimedia Science > IoT Forensics

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Section: G Enabled Iot Environmentsmentioning

confidence: 99%

Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks

Akinbi

2023

WIREs Forensic Science

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“…Mardini et al 33 model the multi‐instance scenario into the context of healthcare monitoring systems. However, the methodology can incur performance loss in other scenarios.…”

Section: Related Workmentioning

confidence: 99%

Energy‐efficient routing in low power and lossy networks with concurrent overlapping RPL instances

Jaisooraj

Kumar

2022

Trans Emerging Tel Tech

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The popularity of the Internet of Things (IoT) has cut across different fields in the information and communication technology domain. Such a remarkable surge in popularity has indeed marked its stamp in the number of IoT applications getting developed. These applications rely on a solid backing in the low power and lossy networks (LLNs), which is a crucial IoT‐enabling technology. This results in more than one application being performed on top of the same network. Such a scenario is mentioned by the Internet Engineering Task Force, in its description regarding the IPv6 routing protocol for LLNs (RPL), as multiple active routing instances sharing an LLN. The issue becomes more interesting when these instances have overlapping sets of nodes. This article presents a novel objective function (OF) named Multi‐OF that enables the creation of an energy‐efficient RPL instance in an LLN with concurrent overlapping instances. The optimization achieved by Multi‐OF can be attributed to the inclusion of a novel metric named packet energy correlation index (PECI) along with expected transmission count. The correlation provided by PECI gives an estimate regarding the ability of a node, in terms of the available residual energy, to handle the packets waiting in its queue (ie, packet buffer). The efficiency of the proposed OF has been justified through simulations conducted using Contiki‐COOJA, the results of which show improvements in terms of power consumption of nodes, packet delivery ratio, number of preferred parent changes per node, packet overhead, end‐to‐end delay, and jitter.

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“…A solution based on an integrated DL algorithm was offered in several articles [185][186][187][188]. The positive samples are extended to balance the number of positive and negative samples, and CT images are pre-processed using image clipping, normalisation, and segmentation.…”

Section: Resource Allocationmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard.

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Using Multiple RPL Instances to Enhance the Performance of New 6G and Internet of Everything (6G/IoE)-Based Healthcare Monitoring Systems

Cited by 23 publications

References 43 publications

Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks

Digital forensics challenges and readiness for 6G Internet of Things (IoT) networks

Energy‐efficient routing in low power and lossy networks with concurrent overlapping RPL instances

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

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