Meeting Delay guarantee in Telemedicine service using SDN framework

Aswanth, A; Manoj, E.; Rajendran, K.; M, Sanjay Krishnan E; Duttagupta, Subhasri

doi:10.1109/r10-htc53172.2021.9641695

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…Using a range of wireless technologies, such as XBee, Wi-Fi, and Bluetooth [76], it uses an efficient frequency spectrum allocation approach that takes network heterogeneity into account. [79] design a three-tiered telemedicine platform to offer prompt medical services.…”

Section: Designing a Telemedicine Networkmentioning

confidence: 99%

“…communications, artificial intelligence methodologies, and techniques, Internet of Things wearable sensors and hardware devices, smartphones, and cloud computing, which all aim to improve telemedicine architecture and design. The following subsections will discuss different telemedicine network architecture design approaches.5.1 Cognitive Radio-Based Telemedicine Network DesignResearchers' interest in the wireless transfer of patient medical data via diverse networks has lately increased.Yet, challenges like efficient frequency spectrum usage and longer gadget lifespans are thought to be the most urgent ones right now[76]. MBANs are now being used in unlicensed frequency bands, where there is a high risk of cross-interference with other electronic devices[77].…”

mentioning

confidence: 99%

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Maximizing Network Capacity, Control and Management in Designing a Telemedicine Network: A Review and Recent Challenges

Sadiq,

Zakariyya,

Buhari

et al. 2024

AfricArXiv

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Telemedicine networks have seen significant changes in their capacity, monitoring, management, and control framework during the previous decades. The evolution of network capacity, control, and management for Unmanned Aerial Vehicle (UAV) & Software-Defined Networks (SDN) as support to telemedicine, artificial intelligence in telemedicine networks, and capabilities in designing a telemedicine network with respect to its performance and customization is presented in this study, with a historical history and a future view. The first section of the article goes over the history of traffic and capacity expansion, as well as future projections. By introducing a medical and image data communication protocol for telemedicine, the second section examines the technological constraints of expanding capacity in the era of UAV & software defined networking. The third section discusses ways to maximize network capacity by considering quality of service (QoS) capacity issues. Finally, the article explores how to construct a telemedicine network that can provide performance, customization, and capabilities to keep up with increased traffic in the coming decades. Research gaps and future directions were presented in the last section.

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Section: Designing a Telemedicine Networkmentioning

confidence: 99%

mentioning

confidence: 99%

Maximizing Network Capacity, Control and Management in Designing a Telemedicine Network: A Review and Recent Challenges

Sadiq,

Zakariyya,

Buhari

et al. 2024

AfricArXiv

View full text Add to dashboard Cite

show abstract

“…Researchers' interest in the wireless transfer of patient medical data via diverse networks has lately increased. Yet, challenges like efficient frequency spectrum usage and longer gadget lifespans are thought to be the most urgent ones right now [76]. MBANs are now being used in unlicensed frequency bands, where there is a high risk of cross-interference with other electronic devices [77].…”

Section: Cognitive Radio-based Telemedicine Network Designmentioning

confidence: 99%

“…A Bio Cog algorithm was also developed to set up cognitive networks for disseminating medical data. Using a range of wireless technologies, such as XBee, Wi-Fi, and Bluetooth [76], it uses an efficient frequency spectrum allocation approach that takes network heterogeneity into account. [79] design a three-tiered telemedicine platform to offer prompt medical services.…”

Section: Cognitive Radio-based Telemedicine Network Designmentioning

confidence: 99%

Maximizing network capacity, control and management in designing a telemedicine network: A review and recent challenges

Sadiq,

Zakariyya,

Buhari

et al. 2024

Nig. J. Tech.

View full text Add to dashboard Cite

Telemedicine networks have seen significant changes in their capacity, monitoring, management, and control framework during the previous decades. The evolution of network capacity, control, and management for Unmanned Aerial Vehicle (UAV) & Software-Defined Networks (SDN) as support to telemedicine, artificial intelligence in telemedicine networks, and capabilities in designing a telemedicine network with respect to its performance and customization is presented in this study, with a historical history and a future view. The first section of the article goes over the history of traffic and capacity expansion, as well as future projections. By introducing a medical and image data communication protocol for telemedicine, the second section examines the technological constraints of expanding capacity in the era of UAV & softwaredefined networking. The third section discusses ways to maximize network capacity by considering quality of service (QoS) capacity issues. Finally, the article explores how to construct a telemedicine network that can provide performance, customization, and capabilities to keep up with increased traffic in the coming decades. Research gaps and future directions were presented in the last section.

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Elephant flow detection intelligence for software-defined networks: a survey on current techniques and future direction

Hamdan,

Elshafie,

Salih

et al. 2024

Evol. Intel.

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Meeting Delay guarantee in Telemedicine service using SDN framework

Cited by 4 publications

References 8 publications

Maximizing Network Capacity, Control and Management in Designing a Telemedicine Network: A Review and Recent Challenges

Maximizing Network Capacity, Control and Management in Designing a Telemedicine Network: A Review and Recent Challenges

Maximizing network capacity, control and management in designing a telemedicine network: A review and recent challenges

Elephant flow detection intelligence for software-defined networks: a survey on current techniques and future direction

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