EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 189 (2018) MATEC Web Conf., 189 (2018) 03011 References
Open Access
Issue
MATEC Web Conf.
Volume 189, 2018
2018 2nd International Conference on Material Engineering and Advanced Manufacturing Technology (MEAMT 2018)
Article Number 03011
Number of page(s) 7
Section Cloud & Network
DOI https://doi.org/10.1051/matecconf/201818903011
Published online 10 August 2018
  1. Kraemer, F.A., Braten, A.E., Tamkittikhun, N., and Palma, D.: ‘Fog Computing in Healthcare–A Review and Discussion’, IEEE Access, 2017, 5, pp. 9206-9222 [CrossRef] [Google Scholar]
  2. Duhigg, C.: ‘The power of habit: Why we do what we do in life and business’ (Random House, 2012) [Google Scholar]
  3. Hellerstein, J.: ‘Parallel programming in the age of big data. Gigaom Blog (2008). [Google Scholar]
  4. Ursum, J., Bos, W.H., van de Stadt, R.J., Dijkmans, B.A., and V.Schaardenburg, ‘Different properties of ACPA and IgM-RF derived from a large dataset: further evidence of two distinct autoantibody systems’, (2009), 11, (3). [Google Scholar]
  5. Cerina, L., Notargiacomo, S., Paccanit, M.G., and Santambrogio, M.D.: ‘A fogcomputing architecture for preventive healthcare and assisted living in smart ambients’, in Editor (Ed.) ^(Eds.): (IEEE, 2017, edn.), pp. 1-6 [Google Scholar]
  6. Manyika, J., Chui, M., Bisson, P., Woetzel, J., Dobbs, R., Bughin, J., and Aharon, D.: ‘Unlocking the Potential of the Internet of Things’, McKinsey Global Institute, 2015 [Google Scholar]
  7. Bauer, H., Patel, M., and Veira, J.: ‘The Internet of Things: Sizing up the opportunity’, Retrieved from: McKinsey in, (2014) [Google Scholar]
  8. Van-Dai Ta, C.-M.L., Goodwill Wandile Nkabinde: ‘Big Data Stream Computing in Healthcare Real-Time Analytics’, IEEE, (2016) [Google Scholar]
  9. Yang Yang, X.Z., Wenzhong Guo, Ximeng Liu, Victor Chang: ‘Privacy-Preserving Fusion of IoT and Big Data for E-health’, (2017) [Google Scholar]
  10. Yang, X.Z., W. Guo, X. Liu,V.Chang: ‘Privacy-preserving smart IoT-based healthcare big data storage and self-adaptive access control system’, ELSEVIER [Google Scholar]
  11. E.Topal: ‘The Creative Destruction of medicine’, (2013) [Google Scholar]
  12. Al-Jarrah, O.Y., Yoo, P.D., Muhaidat, S., Karagiannidis, G.K., and Taha, K.: ‘Efficient machine learning for big data: A review’, Big Data Research, (2015, 2, 3). [CrossRef] [Google Scholar]
  13. V.Palanisamy & R.Thirunavukarasu:‘Implications of Big Data Analytics in developing Healthcare Frameworks–A review’, King Saud University (2017) [Google Scholar]
  14. L.Wang, and C.A. Alexander.: ‘Big data in medical applications and health care’, American Medical Journal, (2015), 6, (1), pp. 1 [Google Scholar]
  15. Zhang, Y., Qiu, M., Tsai, C.-W., Hassan, M.M., and Alamri, A.: ‘Health-CPS: Healthcare cyber-physical system assisted by cloud and big data’, IEEE (2017), 11. [Google Scholar]
  16. Lin, W., Dou, W., Zhou, Z., and Liu, C.: ‘A cloud-based framework for Homediagnosis service over big medical data’, Journal of Systems and Software, (2015).102 [Google Scholar]
  17. He, C., Fan, X., and Li, Y.: ‘Toward ubiquitous healthcare services with a novel efficient cloud platform’, IEEE Transactions on Biomedical Engineering, (2013), 60. [Google Scholar]
  18. Conti, M., Dehghantanha, A., Franke, K., and Watson, S.: ‘Internet of Things security and forensics: Challenges and opportunities’, in Editor (Ed.) ^(Eds.): ‘Book Internet of Things security and forensics: Challenges and opportunities’ (Elsevier, 2018, edn.), pp. [Google Scholar]
  19. Oracevic, A., Dilek, S., and Ozdemir, S.: ‘Security in internet of things: A survey’, in Editor (Ed.) ^(Eds.): ‘Book Security in internet of things: A survey’ (IEEE, 2017, edn.) [Google Scholar]
  20. Mahmud, R., Kotagiri, R., and Buyya, R.: ‘Fog computing: A taxonomy, survey and future directions’: ‘Internet of Everything’ (Springer, 2018), pp. 103-130 [CrossRef] [Google Scholar]
  21. Bonomi, F., Milito, R., Zhu, J., and Addepalli, S.: ‘Fog computing and its role in the internet of things’, in Editor (Ed.) ^(Eds.): ‘Book Fog computing and its role in the internet of things’ (ACM, 2012, edn.), pp. 13-16 [Google Scholar]
  22. Hu, Y.C., Patel, M., Sabella, D., Sprecher, N., and Young, V.: ‘Mobile edge computing–A key technology towards 5G’, ETSI white paper, (2015), 11, pp.1-16 [Google Scholar]
  23. Fernando, N., Loke, S.W., and Rahayu, W.: ‘Mobile cloud computing: A survey’, Future generation computer systems, (2013), 29, (1), pp. 84-106 [Google Scholar]
  24. Barik, R.K., Dubey, H., Misra, … ‘Fog Assisted Cloud Computing in Era of Big Data and Internet-of-Things: Systems, Architectures, and Applications’ (Springer, 2018). [Google Scholar]
  25. Dastjerdi, A.V., and Buyya, R.: ‘Fog computing: Helping the Internet of Things realize its potential’, Computer, (2016), 49, (8), pp. 112-116 [CrossRef] [Google Scholar]
  26. Osanaiye, O., Chen, S., Yan, Z., Lu, R., Choo and Dlodlo, M.: ‘From cloud to fog computing: A review and a conceptual live VM migration framework’, IEEE (2017), 5 [Google Scholar]
  27. Apexa A. Dabhi, P.T.J.R. Prof., K. Chaudhary: ‘Fog computing: A review and conceptual architecture, issues, applications and its challenges’, IJARIIE-ISSN(O)- 2395-4396, (2017), 3 [Google Scholar]
  28. Eide, R.B.: ‘Low Energy Wireless ECG-An exploration of wireless electrocardiography and the utilization of low energy sensors for clinical ambulatory patient monitoring’, NTNU, (2016) [Google Scholar]
  29. Paksuniemi, M., Sorvoja, H., Alasaarela, E., and Myllyla, R.:(IEEE, 2006, edn.) [Google Scholar]
  30. Alesanco, A., and García, J.: ‘Clinical assessment of wireless ECG transmission in real-time cardiac telemonitoring’, IEEE, (2010), 14, (5), pp. 1144-1152 [Google Scholar]
  31. Movassaghi, S., Abolhasan, M., Lipman, J., Smith, D., and Jamalipour, A.: ‘Wireless body area networks: A survey’, IEEE Communications Surveys & Tutorials, (2014) [Google Scholar]
  32. Sametinger, J., and Rozenblit, J.W.: ‘Security Scores for Medical Devices’, in Editor (Ed.) ^(Eds.): ‘Book Security Scores for Medical Devices’ (2016, edn.), pp. 533-541 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.