Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Bauch N (2015) 9 Bodies in the cloud: a geography of electronic health data. Regulating the cloud: policy for computing infrastructure, p 257

  2. Dubey H, Yang J, Constant N, Amiri AM, Yang Q, Makodiya K (2015) Fog Data: enhancing telehealth big data through fog computing. Proc ASE BigData SocialInf 2015:14

    Google Scholar 

  3. Mockus A (2014) Engineering big data solutions. In: Proceedings of the on future of software engineering, pp 85–99

  4. Coakley M, Crocetti G, Dressner P, Kellum W, Lamin T (2015) Transforming telemedicine through big data analytics. arXiv preprint arXiv:1505.06967

  5. Ranjan R, Georgakopoulos D, Wang L (2015) A note on software tools and technologies for delivering smart media-optimized big data applications in the cloud. Computing 1–5

  6. Kuusik A, Reilent E, Loobas I, Parve M (2011) Software architecture for modern telehealth care systems. Adv Inf Sci Serv Sci 3(2)

  7. Stamm BH (1998) Clinical applications of telehealth in mental health care. Prof Psych Res Pract 29(6):536

    Article  Google Scholar 

  8. Priyanka K, Kulennavar N (2014) A survey on Big Data analytics in health care. Int J Comput SciI Inf Technol 5(4):5865–5868

    Google Scholar 

  9. Noel HC, Vogel DC, Erdos JJ, Cornwall D, Levin F (2004) Home telehealth reduces healthcare costs. Telemed J E-Health 10(2):170–183

    Article  Google Scholar 

  10. Hersh WR (2014) Healthcare data analytics. Health informatics: practical guide for healthcare

  11. Paez DG, Aparicio F, de Buenaga M, Ascanio JR (2014) Big data and IoT for chronic patients monitoring. In: Ubiquitous computing and ambient intelligence. Personalisation and user adapted services, pp 416–423

  12. Belle A, Thiagarajan R, Soroushmehr SM, Navidi F, Beard DA, Najarian K (2015) Big data analytics in healthcare. BioMed Res Int

  13. McGregor C (2013) Wearable monitors on babies: big data saving little people. In: 2013 IEEE International Symposium on Technology and Society (ISTAS), Toronto, ON. IEEE. doi:10.1109/ISTAS.2013.6613120

  14. Keh H-C, Hui L, Chou K-Y, Cheng Y-C, Yu P-Y, Huang N-C (2014) Big data generation: application of mobile healthcare. In: Trends and applications in knowledge discovery and data mining, pp 735–743

  15. Li SJ, Te He W, Wang XB, Shi T (2015) Collaborative filtering algorithm for recommendation system of improvement based on big data environment. Appl Mech Mater 736:189–195

    Article  Google Scholar 

  16. McAfee A, Brynjolfsson E, Davenport TH, Patil DJ, Barton D (2012) Big data. The management revolution. Harvard Bus Rev 90(10):61–67

    Google Scholar 

  17. Onyejekwe ER (2014) Big data in health informatics architecture. In: 2014 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM), pp 728–736

  18. Payakachat N, Tilford JM, Ungar WJ (2015) National database for autism research (NDAR): big data opportunities for health services research and health technology assessment. PharmacoEconomics 1–12

  19. Doswell JT (2015) Artificial intelligent psychological counselors for home accessible mental telehealth. In: 142nd APHA annual meeting and exposition APHA

  20. Jang-Jaccard J, Nepal S, Celler B, Yan B (2014) WebRTC-based video conferencing service for telehealth. Computing 1–25

  21. Barnett TE, Chumbler NR, Bruce Vogel W, Beyth RJ, Haijing Qin, Rita Kobb (2006) The effectiveness of a care coordination home telehealth program for veterans with diabetes mellitus: a 2-year follow-up. Am J Manag Care 12(8):467

    Google Scholar 

  22. Wilson LS, Stevenson DR, Cregan P (2010) Telehealth on advanced networks. Telemed e-Health 16(1):69–79

    Article  Google Scholar 

  23. Pickard KT, Swan M (2014) Big desire to share big health data: a shift in consumer attitudes toward personal health information. In: 2014 AAAI Spring Symposium Series

  24. Mukherjee A, Pal A, Misra P (2012) Data analytics in ubiquitous sensor-based health information systems. In: Next generation mobile applications, services and technologies (NGMAST), 2012 6th international conference on, pp 193–198

  25. Nelson R, Staggers N (2013) Health informatics: An interprofessional approach. Elsevier Health Sciences, USA

  26. Finkelstein SM, Speedie SM, Potthoff S (2006) Home telehealth improves clinical outcomes at lower cost for home healthcare. Telemed J e-Health 12(2):128–136

    Article  Google Scholar 

  27. Nickelson DW (1998) Telehealth and the evolving health care system: strategic opportunities for professional psychology. Prof Psychol Res Pract 29(6):527

    Article  Google Scholar 

  28. Brownstein JS, Freifeld CC, Madoff LC (2009) Digital disease detection harnessing the Web for public health surveillance. N Engl J Med 360(21):2153–2157

    Article  Google Scholar 

  29. Vuononvirta T et al (2011) The compatibility of telehealth with health-care delivery. J Telemed Telecare 17(4):190–194

    Article  Google Scholar 

  30. Darkins A, Ryan P, Kobb R, Foster L, Edmonson E, Wakefield B, Lancaster AE (2008) Care Coordination/Home Telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemed e-Health 14(10):1118–1126

    Article  Google Scholar 

  31. Yasir R, Nibir SI, Chadni ZA, Ahmed N (2015) Telemedicine system for financially unstable people of Bangladesh. J Modern Sci Technol 3(1)

  32. Gagnon M-P, Duplantie J, Fortin J-P, Landry R (2006) Implementing telehealth to support medical practice in rural/remote regions: what are the conditions for success 1(1):18

  33. Granda JC, Nuno P, Suarez FJ, Garcia DF (2015) Overlay network based on WebRTC for interactive multimedia communications. In: Computer, information and telecommunication systems (CITS), 2015 international conference on, pp 1–5

  34. Chen Y, Hao H, Chen H, Li L (2015) The study on a telemedicine interaction mode for Deep Brain Stimulation postoperative follow-up. In: Engineering in medicine and biology society (EMBC), 2015 37th annual international conference of the IEEE, pp 186–189

  35. Keen J, Calinescu R, Paige R, Rooksby J (2013) Big data+ politics= open data: the case of health care data in England. Policy Internet 5(2):228–243

    Article  Google Scholar 

  36. Thieffry J, Yamamoto S, Okamoto S, Yamanaka N. A virtual P2P energy management network based on direct-load control for the smart-grids

  37. Kornak J (2016) System requirements for delivery of telemedicine services. In: Telemanagement of inflammatory bowel disease, pp 117–151

  38. Ly SM (2015) Improving HIV-AIDS treatment and adherence through telemedicine

  39. DelliFraine JL, Dansky KH (2008) Home-based telehealth: a review and meta-analysis. J Telemed Telecare 14(2):62–66

    Article  Google Scholar 

  40. Lohrmann B, Kao O (2013) The Nephele livescale toolkit: real-time video stream processing at scale. In: Proc. of the 20th international packet video workshop-posters track, IEEE, San Jose

  41. Chan DS, Callahan CW, Sheets SJ, Moreno CN, Malone Francis J (2003) An Internet-based store-and-forward video home telehealth system for improving asthma outcomes in children. Am J Health Syst Pharm 60(19):1976–1981

    Google Scholar 

  42. Hensel BK, Demiris G, Courtney KL (2006) Defining obtrusiveness in home telehealth technologies. J Am Med Inf Assoc 13(4):428–431

    Article  Google Scholar 

  43. Polisena J, Tran K, Cimon K, Hutton B, McGill S, Palmer K, Scott RE (2010) Home telehealth for chronic obstructive pulmonary disease: a systematic review and meta-analysis. J Telemed Telecare 16(3):120–127

    Article  Google Scholar 

  44. Nancy T (2007) Telehealth as a tool for enhancing care for patients with cardiovascular disease. J Cardiovasc Nurs 22(1):25–31

    Article  Google Scholar 

  45. Ochian A, Suciu G, Fratu O, Voicu C, Suciu V (2014) An overview of cloud middleware services for interconnection of healthcare platforms. In: Communications (COMM), 2014 10th international conference on, pp 1–4

  46. Al-Majeed SS, Al-Mejibli IS, Karam J (2015) Home telehealth by Internet of Things (IoT). In: Electrical and computer engineering (CCECE), 2015 IEEE 28th Canadian conference on, pp 609–613

  47. Ding X, Ren H, Gan Y (2013) Method and apparatus of WebRTC media control. U.S. Patent Application 14/137,322

  48. Holmberg H-C (2015) Web real-time data transport: WebRTC data channels

Download references

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

Authors and Affiliations

  1. School of Electronics and Computer Engineering, Chonnam National University, Gwangju, Korea

    Linh Van Ma, Jisue Kim, Sanghyun Park & Jinsul Kim

  2. IT Convergence Technology Research Laboratory, Real and Emotional Sense Convergence Service Platform Research Section, Electronics and Telecommunications Research Institute, Daejeon, Korea

    Jonghyeon Jang

Authors
  1. Linh Van Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jisue Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sanghyun Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jinsul Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jonghyeon Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jinsul Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-016-1636-8

Keywords

Search

Navigation