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Mobile edge computing based QoS optimization in medical healthcare applications

Author

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  • Sodhro, Ali Hassan
  • Luo, Zongwei
  • Sangaiah, Arun Kumar
  • Baik, Sung Wook

Abstract

Emerging trends in mobile edge computing for developing the efficient healthcare application such as, remote monitoring of the patients with central electronics clouds (e-Clouds) and their increasing voluminous multimedia have caught the attention of everyone in industry and academia. So, clear visualization, big sensing level, and better quality of service (QoS) is the foremost priority. This paper proposes the window-based Rate Control Algorithm (w-RCA) to optimize the medical quality of service (m-QoS) in the mobile edge computing based healthcare by considering the network parameters for instance, peak-to-mean ratio (PMR), standard deviation (Std.dev), delay and jitter during 8 min medical video stream named “Navigation to the Uterine Horn, transection of the horn and re-anastomosis’ transmission over 5 G networks. The performance of the proposed w-RCA is evaluated and compared with the conventional battery smoothing algorithm (BSA) and Baseline by using MPEG-4 encoder for optimizing m-QoS at the source or the server side. The experimental results demonstrate that the w-RCA outperforms the BSA and Baseline by optimizing QoS in remote healthcare application i.e., Tele-surgery. Besides, it is observed and analyzed that w-RCA produces better and effective results at small buffer and window sizes unlike BSA and Baseline by adopting large buffer size during QoS optimization.

Suggested Citation

  • Sodhro, Ali Hassan & Luo, Zongwei & Sangaiah, Arun Kumar & Baik, Sung Wook, 2019. "Mobile edge computing based QoS optimization in medical healthcare applications," International Journal of Information Management, Elsevier, vol. 45(C), pages 308-318.
    • Handle: RePEc:eee:ininma:v:45:y:2019:i:c:p:308-318
    DOI: 10.1016/j.ijinfomgt.2018.08.004
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    References listed on IDEAS

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    Cited by:

    1. Zongpeng Xu & Fuyu Ban & Pasquale Fotia, 2026. "Efficient QoS processing for internet of medical things using non-cooperative game theory: resource allocation in cloud framework," Annals of Operations Research, Springer, vol. 356(1), pages 427-442, January.
    2. Bai Liu & Shuyan Guo & Bin Ding, 2020. "Technical Blossom in Medical Care: The Influence of Big Data Platform on Medical Innovation," IJERPH, MDPI, vol. 17(2), pages 1-17, January.

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