On the feasibility of telesurgery over software defined networks

Mohammadi, Reza; Javidan, Reza

doi:10.1007/s41315-018-0059-5

Cited by 12 publications

(21 citation statements)

References 43 publications

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“…The proposed SDN-based telemedicine architecture ensures the reliable transmission of medical data traffic between the physician and patients. The architecture can help to achieve proper transport protocols for improved QoS in reducing end-to-end delay, packet loss, and jitter during telemedicine health consultations [ 9 ]. The proposed architecture manage telemedicine traffics in an effective manner over SDN-based communication network to achieve QoS.…”

Section: Discussionmentioning

confidence: 99%

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Applying software-defined networking to support telemedicine health consultation during and post Covid-19 era

2020

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The novel coronavirus disease-19 (COVID-19) infection has altered the society, economy, and entire healthcare system. Whilst this pandemic has presented the healthcare system with unprecedented challenges, it has rapidly promoted the adoption of telemedicine to deliver healthcare at a distance. Telemedicine is the use of Information and Communication Technology (ICT) for collecting, organizing, storing, retrieving, and exchanging medical information. But it is faced with the limitations of conventional IP-based protocols which makes it challenging to provide Quality of Service (QoS) for telemedicine due to issues arising from network congestion. Likewise, medical professionals adopting telemedicine are affected with low QoS during health consultations with outpatients due to increased internet usage. Therefore, this study proposes a Software-Defined Networking (SDN) based telemedicine architecture to provide QoS during telemedicine health consultations. This study utilizes secondary data from existing research works in the literature to provide a roadmap for the application of SDN to improve QoS in telemedicine during and after the COVID-19 pandemic. Findings from this study present a practical approach for applying SDN in telemedicine to provide appropriate bandwidth and facilitate real time transmission of medical data.

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Section: Discussionmentioning

confidence: 99%

“…Providing QoS for telemedicine is one of the issues faced in communication networks [ 9 ]. Therefore, this study presents the significance of telemedicine, issues and recommendations of integrating telemedicine for health consultations.…”

Section: Discussionmentioning

confidence: 99%

Applying software-defined networking to support telemedicine health consultation during and post Covid-19 era

2020

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“…A large variety of meta-heuristic algorithms such as ACO [183][184][185][186][187][188][189][190][191], EAs [192][193][194], GAs [195][196][197][198][199][200][201][202][203], PSO [204][205][206][207][208][209], SA [210][211][212], bee colony optimisation-based [213,214], whale optimisation [215,216], FFO [217], BA [85], TLBO [87] and GWO [207] were used in SDN.…”

Section: Meta-heuristic Algorithms Used In Sdnmentioning

confidence: 99%

“…Mohammadi and Javidan [87] used TLBO for providing SDN-based QoS for remote telesurgery applications. The proposed model calculates the optimal path between the surgeon and operating room based on network resources status.…”

Section: Tlbo In Sdnmentioning

confidence: 99%

“…TLBO [86] is a new population‐based algorithm basically proposed for constrained mechanical design optimisation problems. In TLBO, a set of learners is defined as population, and the optimal solution in the population is considered as the teacher [87]. TLBO needs merely the population size and the number of iterations as the control parameters [87].…”

Section: Artificial Intelligencementioning

confidence: 99%

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Artificial intelligence enabled software‐defined networking: a comprehensive overview

Latah

Toker

2019

IET Networks

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Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

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FRT-SDN: an effective firm real time routing for SDN by early removal of late packets

Sedaghat

Jahangir

2022

Telecommun Syst

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On the feasibility of telesurgery over software defined networks

Cited by 12 publications

References 43 publications

Applying software-defined networking to support telemedicine health consultation during and post Covid-19 era

Applying software-defined networking to support telemedicine health consultation during and post Covid-19 era

Artificial intelligence enabled software‐defined networking: a comprehensive overview

FRT-SDN: an effective firm real time routing for SDN by early removal of late packets

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