Advertisement

Emergency-level-based healthcare information offloading over fog network

  • Cong Zhang
  • Hsin-Hung ChoEmail author
  • Chi-Yuan Chen
Article
  • 60 Downloads

Abstract

Recently, the healthcare technologies continue to develop rapidly, especially various wearable Internet of Things (IoT) devices for body network have been invented one after another. The relevant products can already be easily purchased in the market such as the smart bracelet, smart blood pressure monitor and so on. These healthcare devices not only make users able to understand their own body information more in more detail but also provide a communication way to the hospital. It means that patients can obtain the professional medical prescription advice without going to the hospital in person because the health information can transmit to the medical cloud through any network interfaces. Additionally, both medical records of patients and prescription advice from doctors are stored in the cloud. In order to provide the better service quality, the use of fog in the network edge can quickly response the requests from the patients. The computing power of the fog node is less than the cloud. Therefore, balancing the trade-off between cloud and fog is very important. In this paper, we formulate an optimization problem about offloading then use the metaheuristic to find out the best policy. Moreover, we also design an emergency supporting measure. Simulation results show that the proposed methods can provide a more efficient healthcare service.

Keywords

Healthcare Fog network Offloading 

Notes

Acknowledgements

This research was partly funded by the National Science Council of the R.O.C. under grants MOST 107-2221-E-197-005-MY3.

References

  1. 1.
    Xu B, Da Xu L, Cai H, Xie C, Hu J, Bu F (2014) Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Trans Ind Inf 10(2):1578–1586CrossRefGoogle Scholar
  2. 2.
    Ma Y -J, Zhang Y, Dung O M, Li R, Zhang D -Q (2015) Health internet of things: recent applications and outlook. Int J Intell Technol 16(2):351–362Google Scholar
  3. 3.
    Li T-M, Liao C-C, Cho H-H, Chien W-C, Lai C-F, Chao H-C (2017) An e-healthcare sensor network load-balancing scheme using SDN-SFC. In: Proceedings of IEEE 19th international conference on e-health networking, applications and services (Healthcom’17), pp 1–4Google Scholar
  4. 4.
    Hamalainen M, Pirinen P, Iinatti J (2008) Taparugssanagorn, A UWB supporting medical ICT applications. In: Proceedings of IEEE international conference on ultra-wideband’08. ICUWB 2008, pp 15–16Google Scholar
  5. 5.
    Sung WT, Chiang YC (2012) Improved particle swarm optimization algorithm for android medical care IOT using modified parameters. J Med Syst 36(6):3755–3763CrossRefGoogle Scholar
  6. 6.
    Rohokale VM, Prasad NR, Prasad R (2011) A cooperative internet of things (IoT) for rural healthcare monitoring and control. In: Proceedings of 2nd international conference on wireless communication, vehicular technology, information theory and aerospace & electronic systems technology (Wireless VITAE’11), pp 1–6Google Scholar
  7. 7.
    Liu Y, Niu J, Yang L, Shu L (2014) eBPlatform: an IoT-based system for NCD patients homecare in China. In: Proceedings of IEEE global communications conference (GLOBECOM’14), pp 2448– 2453Google Scholar
  8. 8.
    Amendola S, Lodato R, Manzari S, Occhiuzzi C, Marrocco G (2014) RFID technology for IoT-based personal healthcare in smart spaces. IEEE Internet Things J 1(2):144–152CrossRefGoogle Scholar
  9. 9.
    Wan J, Zou C, Ullah S, Lai C-F, Zhou M, Wang X (2013) Cloud-enabled wireless body area networks for pervasive healthcare. IEEE Netw 27(5):56–61CrossRefGoogle Scholar
  10. 10.
    Tseng F-H, Cho H-H, Chang K-D, Li J-C, Shih TK (2018) Application-oriented offloading in heterogeneous networks for mobile cloud computing. Enterp Inf Syst 12(4):398– 413CrossRefGoogle Scholar
  11. 11.
    Kitanov S, Janevski T (2018) Fog computing service orchestration mechanisms for 5G networks. J Internet Technol 19(1):297– 305Google Scholar
  12. 12.
    Amazing Healthcare Technology Innovations in 2016 (2016) https://getreferralmd.com/2016/01/healthcare-technology-2016/
  13. 13.
    Fukuda O, Takahashi Y, Bu N, Okumura H, Arai K (2017) Development of an IoT-based prosthetic control system. J Rob Mechatronics 29(6):1049–1056CrossRefGoogle Scholar
  14. 14.
    Balsalobre-Fernández C, Kuzdub M, Poveda-Ortiz P, del Campo-Vecino J (2016) Validity and reliability of the push wearable device to measure movement velocity during the back squat exercise. J Strength Cond Res 30 (7):1968–1974CrossRefGoogle Scholar
  15. 15.
    Kuo CE, Liu YC, Chang DW, Young CP, Shaw FZ, Liang SF (2017) Development and evaluation of a wearable device for sleep quality assessment. IEEE Trans Biomed Eng 64(7):1547– 1557CrossRefGoogle Scholar
  16. 16.
    Yi S, Li C, Li Q (2015) A survey of fog computing: concepts, applications and issues. In: Proceedings of the 2015 workshop on mobile big data, pp 37–42Google Scholar
  17. 17.
    Cho HH, Lai CF, Shih TK, Chao HC (2016) Learning-based data envelopment analysis for external cloud resource allocation. Mobile Netw Appl 21(5):846–855CrossRefGoogle Scholar
  18. 18.
    Zhang W, Zhang Z, Chao H C (2017) Cooperative fog computing for dealing with big data in the internet of vehicles: architecture and hierarchical resource management. IEEE Commun Mag 55(12):60–67CrossRefGoogle Scholar
  19. 19.
    Luan TH, Gao L, Li Z, Xiang Y, Wei G, Sun L (2015) Fog computing: focusing on mobile users at the edge. arXiv:1502.01815
  20. 20.
    Bao W, Yuan D, Yang Z, Wang S, Li W, Zhou BB, Zomaya AY (2017) Follow me fog: toward seamless handover timing schemes in a fog computing environment. IEEE Commun Mag 55(11):72–78CrossRefGoogle Scholar
  21. 21.
    Lyu L, Nandakumar K, Rubinstein B, Jin J, Bedo J, Palaniswami M (2018) PPFA: Privacy preserving fog-enabled aggregation in smart grid. IEEE Transactions on Industrial InformaticsGoogle Scholar
  22. 22.
    Chiang M, Zhang T (2016) Fog and IoT: an overview of research opportunities. IEEE Internet Things J 3 (6):854–864CrossRefGoogle Scholar
  23. 23.
    Ziegeldorf JH, Morchon OG, Wehrle K (2014) Privacy in the internet of things: threats and challenges. Secur Commun Netw 7(12):2728–2742CrossRefGoogle Scholar
  24. 24.
    Yu CM, Chen CY, Chao HC (2017) Privacy-preserving multikeyword similarity search over outsourced cloud data. IEEE Syst J 11(2):385–394CrossRefGoogle Scholar
  25. 25.
    Beyene YD, Jantti R, Tirkkonen O, Ruttik K, Iraji S, Larmo A, Torsner J (2017) NB-IoT technology overview and experience from cloud-RAN implementation. IEEE Wirel Commun 24(3):26–32CrossRefGoogle Scholar
  26. 26.
    Mathur A, Newe T, Rao M (2016) Defence against black hole and selective forwarding attacks for medical WSNs in the IoT. Sensors 16(1):118CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematics and Computer ScienceWuhan Polytechnic UniversityWuhanChina
  2. 2.Department of Computer Science and Information EngineeringNational Ilan UniversityYilanTaiwan

Personalised recommendations