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Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center

Journal of Medical Systems volume 40, Article number: 214 (2016) Cite this article

Abstract

With the development of IoT (Internet of Thing), big data analysis and cloud computing, traditional medical information system integrates with these new technologies. The establishment of cloud-based smart healthcare application gets more and more attention. In this paper, semi-physical simulation technology is applied to cloud-based smart healthcare system. The Body sensor network (BSN) of system transmit has two ways of data collection and transmission. The one is using practical BSN to collect data and transmitting it to the data center. The other is transmitting real medical data to practical data center by simulating BSN. In order to transmit real medical data to practical data center by simulating BSN under semi-physical simulation environment, this paper designs an OPNET packet structure, defines a gateway node model between simulating BSN and practical data center and builds a custom protocol stack. Moreover, this paper conducts a large amount of simulation on the real data transmission through simulation network connecting with practical network. The simulation result can provides a reference for parameter settings of fully practical network and reduces the cost of devices and personnel involved.

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References

  1. Liu, C. H., Fan, J., Branch, J. W., Leung, K. K., Toward qoi and energy-efficiency in internet-of-things sensory environments. IEEE Transactions on Emerging Topics in Computing 2(4):473–487, 2014.

    Article  Google Scholar 

  2. Liu, C. H., Yang, B., Liu, T., Efficient naming, addressing and profile services in internet-of-things sensory environments. Ad Hoc Netw. 18:85–101, 2014.

    Article  Google Scholar 

  3. Zheng, K., Yang, Z., Zhang, K., Chatzimisios, P., Yang, K., Xiang, W., Big data-driven optimization for mobile networks toward 5g. IEEE Netw. 30(1):44–51, 2016.

    Article  Google Scholar 

  4. Chen, M., Mao, S., Liu, Y., Big data: A survey. Mobile Networks and Applications 19(2):171–209, 2014.

    Article  Google Scholar 

  5. Chen, M., Hao, Y., Li, Y., Lai, C. -F., Wu, D., On the computation offloading at ad hoc cloudlet: architecture and service modes. IEEE Commun. Mag. 53(6):18–24, 2015.

    Article  Google Scholar 

  6. Bouwmeester, W., Twisk, J. W., Kappen, T. H., van Klei, W. A., Moons, K. G., Vergouwe, Y., Prediction models for clustered data: comparison of a random intercept and standard regression model. BMC Med. Res. Methodol. 13(1):1, 2013.

    Article  Google Scholar 

  7. Liu, C. H., Wen, J., Yu, Q., Yang, B., Wang, W.: Healthkiosk: A family-based connected healthcare system for long-term monitoring. In: Computer Communications Workshops (INFOCOM WKSHPS), 2011 IEEE Conference on.1em plus 0.5em minus 0.4emIEEE, pp. 241–246 (2011)

  8. Raghupathi, W., and Raghupathi, V., Big data analytics in healthcare: promise and potential. Health Information Science and Systems 2(1):1, 2014.

    Article  Google Scholar 

  9. Lin, K., Wang, W., Wang, X., Ji, W., Wan, J., Qoe-driven spectrum assignment for 5g wireless networks using sdr. IEEE Wirel. Commun. 22(6):48–55, 2015.

    Article  Google Scholar 

  10. Lin, K., Xu, T., Song, J., Qian, Y., Sun, Y.: Node scheduling for all-directional intrusion detection in sdr-based 3d wsns

  11. Qiu, M., Ming, Z., Li, J., Gai, K., Zong, Z., Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans. Comput. 64(12):3528–3540, 2015.

    Article  Google Scholar 

  12. Chen, M., Hao, Y., Qiu, M., Song, J., Wu, D., Humar, I., Mobility-aware Caching and Computation Offloading in 5G Ultradense Cellular Networks. Sensors 16(7):974–987, 2016.

    Article  PubMed Central  Google Scholar 

  13. Chen, M., Zhang, Y., Hu, L., Taleb, T., Sheng, Z., Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies. ACM/Springer Mobile Networks and Applications 20(6):704–712, Dec. 2015.

  14. Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., Escobar, G., Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. 33(7):1123–1131, 2014.

    Article  Google Scholar 

  15. Zhou, L., Specific versus diverse computing in media cloud. IEEE Trans. Circuits Syst. Video Technol. 25 (12):1888–1899, 2015.

    Article  Google Scholar 

  16. Zhou, L., and Wang, H., Toward blind scheduling in mobile media cloud: Fairness, simplicity, and asymptotic optimality. IEEE Trans. Multimedia 15(4):735–746, 2013.

    Article  Google Scholar 

  17. Lei, L., Zhong, Z., Zheng, K., Chen, J., Meng, H., Challenges on wireless heterogeneous networks for mobile cloud computing. IEEE Wirel. Commun. 20(3):34–44, 2013.

    Article  Google Scholar 

  18. Fortino, G., Di Fatta, G., Pathan, M., Vasilakos, A. V., Cloud-assisted body area networks: state-of-the-art and future challenges. Wirel. Netw 20(7):1925–1938, 2014.

    Article  Google Scholar 

  19. Fortino, G., Parisi, D., Pirrone, V., Di Fatta, G., Bodycloud: A saas approach for community body sensor networks. Futur. Gener. Comput. Syst. 35:62–79, 2014.

    Article  Google Scholar 

  20. Qiu, M., Chen, Z., Ming, Z., Qin, X., Niu, J.: Energy-aware data allocation with hybrid memory for mobile cloud systems (2014)

  21. Chen, M., Ma, Y., Song, J., Lai, C., Hu, B., Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring. ACM/Springer Mobile Networks and Applications. doi:10.1007/s11036-016-0745-1,2016..

  22. Tian, D., Zhou, J., Sheng, Z., Leung, V.: Robust energy-efficient mimo transmission for cognitive vehicular networks (2015)

  23. Tian, D., Zhou, J., Wang, Y., Zhang, G., Xia, H., An adaptive vehicular epidemic routing method based on attractor selection model. Ad Hoc Netw. 36:465–481, 2016.

    Article  Google Scholar 

  24. Tian, D., Zhou, J., Wang, Y., Lu, Y., Xia, H., Yi, Z., A dynamic and self-adaptive network selection method for multimode communications in heterogeneous vehicular telematics. IEEE Trans. Intell. Transp. Syst. 16(6):3033–3049, 2015.

    Article  Google Scholar 

  25. Li, Y., Dai, W., Ming, Z., Qiu, M., Privacy protection for preventing data over-collection in smart city. IEEE Trans. Comput. 65(5):1339–1350, 2016.

    Article  Google Scholar 

  26. Liu, C. H., Fan, J., Hui, P., Wu, J., Leung, K. K., Toward qoi and energy efficiency in participatory crowdsourcing. IEEE Trans. Veh. Technol. 64(10):4684–4700, 2015.

    Article  Google Scholar 

  27. Liu, C. H., Hui, P., Branch, J. W., Bisdikian, C., Yang, B.: Efficient network management for context-aware participatory sensing. In: Sensor, mesh and ad hoc communications and networks (secon), 2011 8th annual ieee communications society conference on.1em plus 0.5em minus 0.4emIEEE, pp. 116–124 (2011)

  28. Zhang, B., Song, Z., Liu, C. H., Ma, J., Wang, W., An event-driven qoi-aware participatory sensing framework with energy and budget constraints. ACM Trans. Intell. Syst. Technol. 6(3):42, 2015.

    CAS  Google Scholar 

  29. Liu, C. H., Leung, K. K., Gkelias, A., A generic admission-control methodology for packet networks. IEEE Trans. Wirel. Commun. 13(2):604–617, 2014.

    Article  Google Scholar 

  30. Taleb, T., Ksentini, A., Chen, M., Jantti, R., Coping with emerging mobile social media applications through dynamic service function chaining. IEEE Trans. Wirel. Commun. 15(4):2859–2871, 2016.

    Article  Google Scholar 

  31. Zhang, Y., Chen, M., Mao, S., Hu, L., Leung, V. C., Cap Community activity prediction based on big data analysis. IEEE Netw. 28(4):52–57, 2014.

    Article  Google Scholar 

  32. Bottura, R., Babazadeh, D., Zhu, K., Borghetti, A., Nordström, L., Nucci, C. A.: Sitl and hla co-simulation platforms: Tools for analysis of the integrated ict and electric power system. In: EUROCON, 2013 IEEE.1em plus 0.5em minus 0.4emIEEE, pp. 918–925 (2013)

  33. Chen, M., Opnet network simulation. Vol. 1: Press of Tsinghua University, 2004.

  34. Luo, T., Tan, H. -P., Quek, T. Q., Sensor openflow: Enabling software-defined wireless sensor networks. IEEE Commun. Lett. 16(11):1896–1899, 2012.

    Article  Google Scholar 

  35. Lin, K., Song, J., Luo, J., Ji, W., Hossain, M. S., Ghoneim, A.: Gvt: Green video transmission in the mobile cloud networks

  36. Lin, K., Chen, M., Deng, J., Hassan, M. M., Fortino, G.: Enhanced fingerprinting and trajectory prediction for iot localization in smart buildings

  37. Hossain, M. S.: Cloud-supported cyber–physical localization framework for patients monitoring (2015)

  38. Fortino, G., Galzarano, S., Gravina, R., Li, W., A framework for collaborative computing and multi-sensor data fusion in body sensor networks. Information Fusion 22:50–70, 2015.

    Article  Google Scholar 

  39. Fortino, G., Giannantonio, R., Gravina, R., Kuryloski, P., Jafari, R., Enabling effective programming and flexible management of efficient body sensor network applications. IEEE Transactions on Human-Machine Systems 43(1):115–133, 2013.

    Article  Google Scholar 

  40. Jonnagaddala, J., Liaw, S. -T., Ray, P., Kumar, M., Chang, N. -W., Dai, H. -J., Coronary artery disease risk assessment from unstructured electronic health records using text mining. J. Biomed. Inform. 58: S203–S210, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Chen, M., OPNET IoT Simulation , Huazhong University of Science and Technology Press, ISBN 978-7-5609-9510-6, 2015.

  42. Hossain, M. S., Muhammad, G., Alhamid, M. F., Song, B., Al-Mutib, K., Audio-visual emotion recognition using big data towards 5g. Mobile Networks and Applications,1–11, 2016.

  43. http://www.nsnam.org/

  44. http://omnetpp.org/

  45. http://www.winpcap.org/

  46. Hakiri, A., Gokhale, A., Berthou, P., Schmidt, D. C., Gayraud, T., Software-defined networking: Challenges and research opportunities for future internet. Comput. Netw. 75:453–471 , 2014.

    Article  Google Scholar 

  47. McKeown, N., Software-defined networking. INFOCOM keynote talk 17(2):30–32, 2009.

    Google Scholar 

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Acknowledgments

The authors would like to extend their sincere appreciations to the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia for its funding of this research through the Profile Research Group project (PRG-1436-17).

Author information

Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Xiaobo Shi, Wei Li & Jeungeun Song

  2. College of Computer and Information Engineering, Henan Normal University, Xinxiang, 453007, China

    Xiaobo Shi

  3. Software Engineering Department, College of Computer and Information Science, King Saud University, Riyadh, 11543, Saudi Arabia

    M. Shamim Hossain & Abdulhameed Alelaiwi

  4. Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, 11543, Saudi Arabia

    Sk Md Mizanur Rahman

Authors
  1. Xiaobo Shi
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  2. Wei Li
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  3. Jeungeun Song
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  4. M. Shamim Hossain
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  5. Sk Md Mizanur Rahman
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  6. Abdulhameed Alelaiwi
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Corresponding author

Correspondence to Jeungeun Song.

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This article is part of the Topical Collection on Mobile & Wireless Health

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Cite this article

Shi, X., Li, W., Song, J. et al. Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center. J Med Syst 40, 214 (2016). https://doi.org/10.1007/s10916-016-0575-5

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  • DOI: https://doi.org/10.1007/s10916-016-0575-5

Keywords

  • Semi-physical simulation
  • Big data analysis
  • Body sensor networks
  • Health care