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An efficient Session_Weight load balancing and scheduling methodology for high-quality telehealth care service based on WebRTC

Abstract

In the modern life, humans are more interested in their health care; they usually go to the hospital for taking a treatment traditionally, for more convenience, a telecommunication and information technology, telemedicine provide clinical health care at a distance where physicians use email to communicate with patients, order drug prescriptions, and other health services. However, the system is of not much facility in the busy lives nowadays; hence a new telehealth system is recently developed to deliver health-related services and information with one of the most advanced telecommunications technology, WebRTC. Though, we still deal with many problems when the streaming data in some users become big, an existing network structure is susceptible to a large traffic with WebRTC and may cause overloading problems become big streaming data, where data transmits and concentrates on the specific server device in telehealth care service. Thus, we proposed an efficient Session_Weight load balancing and scheduling methodology to improve network performance for telehealth care service based on WebRTC. In this, we assign a weight session for each participant in the network, after that, we make a scheduling algorithm for distributing packages aiming to equalize the traffic network. Furthermore, we prove that our proposed methodology has a high-quality performance evaluation of telehealth care service, we also compare both kinds of technique, one is the original WebRTC technology, and another one is the existing WebRTC network with load balancing and scheduling network, which applied Session Weight.

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Acknowledgments

This work was supported by ‘The Cross-Ministry Giga KOREA Project’ Grant from the Ministry of Science, ICT and Future Planning, Korea.

Author information

Correspondence to Jinsul Kim.

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Ma, L.V., Kim, J., Park, S. et al. An efficient Session_Weight load balancing and scheduling methodology for high-quality telehealth care service based on WebRTC. J Supercomput 72, 3909–3926 (2016). https://doi.org/10.1007/s11227-016-1636-8

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Keywords

  • Telehealth care
  • WebRTC
  • Big data
  • Load balancing
  • Scheduling
  • Real-time streaming
  • Eye tracking