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Fog Computing Architectures and Frameworks for Healthcare 4.0

  • Anuja R. NairEmail author
  • Sudeep Tanwar
Chapter
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Part of the Signals and Communication Technology book series (SCT)

Abstract

Fog computing environment is geographically dispersed and diverse heterogeneous devices are associated ubiquitously to it towards the end of a system so as to give cooperatively variable and adaptable communication, storage devices, and computation. Fog computing has numerous recompenses and is well-matched for the applications, wherein time-sensitivity, higher response time, and lower latency are absolutely important factors, particularly healthcare applications. These applications also have lot of challenges such as need of remote monitoring of patients, need of preventive instead of reactive care, etc. In many studies, cloud computing was shown to be well suited for healthcare applications, but with advent of fog computing, fog computing imposes more advantages as compared to cloud computing. Many studies showed that fog computing is well-matched for healthcare applications as it facilitates low latency, higher response time, reliability, scalability, location awareness, better security and privacy of health data, fault tolerance, etc. This study is divided into collection of frameworks developed for healthcare application with respect to fog computing and collection of proposed architectures and implemented systems for the same. Researchers have shown through simulations and experiments that the main factor in healthcare application is reduced latency which should be achieved by means of fog computing.

Keywords

Internet of Things (IoT) Fog computing Cloud computing Industry 4.0 Healthcare 4.0 Latency Security Privacy Location awareness Time-sensitivity 

References

  1. 1.
    Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242.Google Scholar
  2. 2.
    Bloem, J., Menno V.D., Sander D., David E., René M., & Erik, V.O. (2014). The fourth industrial revolution. Things Tighten 8.Google Scholar
  3. 3.
    Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.Google Scholar
  4. 4.
    Market pulse report, IoT, Growth enabler. Retrieved April 2017, from https://growthenabler.com/flipbook/pdf/IOT%20Report.pdf
  5. 5.
    Pang, Z., Yang, G., Khedri, R., & Zhang, Y. T. (2018). Introduction to the special section: Convergence of automation technology, biomedical engineering, and health informatics toward the healthcare 4.0. IEEE Reviews in Biomedical Engineering, 11, 249–259.Google Scholar
  6. 6.
    Pang, Z., Yang, G., Khedri, R., & Zhang, Y. T. (2018). Introduction to the special section: Convergence of automation technology, biomedical engineering, and health informatics toward the healthcare 4.0. IEEE Reviews in Biomedical Engineering, 11, 249–259.Google Scholar
  7. 7.
    Biostamp. (2016). https://www.mc10inc.com/
  8. 8.
    Farandos, N. M., Yetisen, A. K., Monteiro, M. J., Lowe, C. R., & Yun, S. H. (2015). Contact lens sensors in ocular diagnostics. Advanced Healthcare Materials, 4(6), 792–810.Google Scholar
  9. 9.
    Sultan, N. (2014). Making use of cloud computing for healthcare provision: Opportunities and challenges. International Journal of Information Management, 34(2), 177–184.Google Scholar
  10. 10.
    Apostu, A., Puican, F., Ularu, G., Suciu, G., & Todoran, G. (2013). Study on advantages and disadvantages of Cloud Computing—the advantages of telemetry applications in the cloud. In Recent advances in applied computer science and digital services.Google Scholar
  11. 11.
    Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing (pp. 13–16). New York, NY: ACM.Google Scholar
  12. 12.
    Khan, S., Parkinson, S., & Qin, Y. (2017). Fog computing security: A review of current applications and security solutions. Journal of Cloud Computing, 6(1), 19.Google Scholar
  13. 13.
    Deng, R., Lu, R., Lai, C., & Luan, T. H. (2015). Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing. In 2015 IEEE International Conference on Communications (ICC) (pp. 3909–3914). Piscataway, NJ: IEEE.Google Scholar
  14. 14.
    Vaquero, L. M., & Rodero-Merino, L. (2014). Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Computer Communication Review, 44(5), 27–32.Google Scholar
  15. 15.
    Bertini, M., Marcantoni, L., Toselli, T., & Ferrari, R. (2016). Remote monitoring of implantable devices: Should we continue to ignore it? International Journal of Cardiology, 202, 368–377.Google Scholar
  16. 16.
    Wise, A., MacIntosh, E., Rajakulendran, N., & Khayat, Z. (2016). Transforming health: Shifting from reactive to proactive and predictive care. Toronto, ON: MaRS.Google Scholar
  17. 17.
    Bilal, K., Khalid, O., Erbad, A., & Khan, S. U. (2018). Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers. Computer Networks, 130, 94–120.Google Scholar
  18. 18.
    Escamilla-Ambrosio, P. J., Rodríguez-Mota, A., Aguirre-Anaya, E., Acosta-Bermejo, R., & Salinas-Rosales, M. (2018) Distributing Computing in the internet of things: cloud, fog and edge computing overview. In NEO 2016 (pp. 87–115). Cham: Springer.Google Scholar
  19. 19.
    Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., et al. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78, 641–658.Google Scholar
  20. 20.
    Kraemer, F. A., Braten, A. E., Tamkittikhun, N., & Palma, D. (2017). Fog computing in healthcare—a review and discussion. IEEE Access, 5, 9206–9222.Google Scholar
  21. 21.
    Hu, P., Dhelim, S., Ning, H., & Qiu, T. (2017). Survey on fog computing: Architecture, key technologies, applications and open issues. Journal of Network and Computer Applications, 98, 27–42.Google Scholar
  22. 22.
    Atlam, H. F., Walters, R. J., & Wills, G. B. (2018). Fog computing and the internet of things: A review. Big Data and Cognitive Computing, 2(2), 10.Google Scholar
  23. 23.
    Mutlag, A. A., Ghani, M. K. A., Arunkumar, N. A., Mohamed, M. A., & Mohd, O. (2019). Enabling technologies for fog computing in healthcare IoT systems. Future Generation Computer Systems, 90, 62–78.Google Scholar
  24. 24.
    Nishio, T., Shinkuma, R., Takahashi, T., & Mandayam, N. B. (2013). Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud. In Proceedings of the First International Workshop on Mobile Cloud Computing and Networking (pp. 19–26). New York, NY: ACM.Google Scholar
  25. 25.
    Kliem, A., & Kao, O. (2015). The Internet of Things resource management challenge. In 2015 IEEE International Conference on Data Science and Data Intensive Systems (pp. 483–490). Piscataway, NJ: IEEE.Google Scholar
  26. 26.
    Lubamba, C., & Bagula, A. (2017). Cyber-healthcare cloud computing interoperability using the HL7-CDA standard. In 2017 IEEE Symposium on Computers and Communications (ISCC) (pp. 105–110). Piscataway, NJ: IEEE.Google Scholar
  27. 27.
    Abu-Elkheir, M., Hassanein, H. S., & Oteafy, S. M. (2016). Enhancing emergency response systems through leveraging crowdsensing and heterogeneous data. In 2016 International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 188–193). Piscataway, NJ: IEEE.Google Scholar
  28. 28.
    Farris, I., Orsino, A., Militano, L., Iera, A., & Araniti, G. (2018). Federated IoT services leveraging 5G technologies at the edge. Ad Hoc Networks, 68, 58–69.Google Scholar
  29. 29.
    Ryden, M., Oh, K., Chandra, A., & Weissman, J. (2014). Nebula: Distributed edge cloud for data intensive computing. In 2014 IEEE International Conference on Cloud Engineering (pp. 57–66). Piscataway, NJ: IEEE.Google Scholar
  30. 30.
    Zhang, Q., Zhang, X., Zhang, Q., Shi, W., & Zhong, H. (2016). Firework: Big data sharing and processing in collaborative edge environment. In 2016 Fourth IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb) (pp. 20–25). Piscataway, NJ: IEEE.Google Scholar
  31. 31.
    Dubey, H., Yang, J., Constant, N., Amiri, A. M., Yang, Q., & Makodiya, K. (2015). Fog data: Enhancing telehealth big data through fog computing. In Proceedings of the ASE Bigdata and Socialinformatics 2015 (p. 14). New York, NY: ACM.Google Scholar
  32. 32.
    Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., et al. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78, 641–658.Google Scholar
  33. 33.
    Garcia-de-Prado, A., Ortiz, G., & Boubeta-Puig, J. (2017). COLLECT: COLLaborativE ConText-aware service oriented architecture for intelligent decision-making in the Internet of Things. Expert Systems with Applications, 85, 231–248.Google Scholar
  34. 34.
    Kumari, A., Tanwar, S., Tyagi, S., & Kumar, N. (2018). Fog computing for Healthcare 4.0 environment: Opportunities and challenges. Computers & Electrical Engineering, 72, 1–13.Google Scholar
  35. 35.
    Monteiro, A., Dubey, H., Mahler, L., Yang, Q., & Mankodiya, K. (2016). Fit: A fog computing device for speech tele-treatments. In 2016 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 1–3). Piscataway, NJ: IEEE.Google Scholar
  36. 36.
    Manogaran, G., Varatharajan, R., Lopez, D., Kumar, P. M., Sundarasekar, R., & Thota, C. (2018). A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generation Computer Systems, 82, 375–387.Google Scholar
  37. 37.
    Zohora, F. T., Khan, M. R. R., Bhuiyan, M. F. R., & Das, A. K. (2017). Enhancing the capabilities of IoT based fog and cloud infrastructures for time sensitive events. In 2017 International Conference on Electrical Engineering and Computer Science (ICECOS) (pp. 224–230). Piscataway, NJ: IEEE.Google Scholar
  38. 38.
    Sahni, Y., Cao, J., Zhang, S., & Yang, L. (2017). Edge Mesh: A new paradigm to enable distributed intelligence in Internet of Things. IEEE Access, 5, 16441–16458.Google Scholar
  39. 39.
    Oueis, J., Strinati, E. C., Sardellitti, S., & Barbarossa, S. (2015). Small cell clustering for efficient distributed fog computing: A multi-user case. In 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall) (pp. 1–5). Piscataway, NJ: IEEE.Google Scholar
  40. 40.
    Rahman, A., Hassanain, E., & Hossain, M. S. (2017). Towards a secure mobile edge computing framework for Hajj. IEEE Access, 5, 11768–11781.Google Scholar
  41. 41.
    Li, J., Jin, J., Yuan, D., Palaniswami, M., & Moessner, K. (2015). EHOPES: Data-centered Fog platform for smart living. In 2015 International Telecommunication Networks and Applications Conference (ITNAC) (pp. 308–313). Piscataway, NJ: IEEE.Google Scholar
  42. 42.
    Dupont, C., Giaffreda, R., & Capra, L. (2017). Edge computing in IoT context: Horizontal and vertical Linux container migration. In 2017 Global Internet of Things Summit (GIoTS) (pp. 1–4). Piscataway, NJ: IEEE.Google Scholar
  43. 43.
    Wu, D., Liu, S., Zhang, L., Terpenny, J., Gao, R. X., Kurfess, T., et al. (2017). A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing. Journal of Manufacturing Systems, 43, 25–34.Google Scholar
  44. 44.
    Vora, J., Kaneriya, S., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019). TILAA: Tactile internet-based ambient assistant living in fog environment. Future Generation Computer Systems, 98, 635–649.Google Scholar
  45. 45.
    Gia, T. N., Jiang, M., Sarker, V. K., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2017). Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes. In 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 1765–1770). Piscataway, NJ: IEEE.Google Scholar
  46. 46.
    Chakraborty, S., Bhowmick, S., Talaga, P., & Agrawal, D. P. (2016). Fog networks in healthcare application. In 2016 IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) (pp. 386–387). Piscataway, NJ: IEEE.Google Scholar
  47. 47.
    Sood, S. K., & Mahajan, I. (2017). Wearable IoT sensor based healthcare system for identifying and controlling chikungunya virus. Computers in Industry, 91, 33–44.Google Scholar
  48. 48.
    Vora, J., Tanwar, S., Tyagi, S., Kumar, N., & Rodrigues, J. J. (2017). FAAL: Fog computing-based patient monitoring system for ambient assisted living. In 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom) (pp. 1–6). Piscataway, NJ: IEEE.Google Scholar
  49. 49.
    Azimi, I., Anzanpour, A., Rahmani, A. M., Pahikkala, T., Levorato, M., Liljeberg, P., et al. HiCH: Hierarchical fog-assisted computing architecture for healthcare IoT. ACM Transactions on Embedded Computing Systems (TECS), 16(5s), 174.Google Scholar
  50. 50.
    Ahmad, M., Amin, M. B., Hussain, S., Kang, B. H., Cheong, T., & Lee, S. (2016). Health fog: A novel framework for health and wellness applications. The Journal of Supercomputing, 72(10), 3677–3695.Google Scholar
  51. 51.
    Elmisery, A. M., Rho, S., & Aborizka, M. (2019). A new computing environment for collective privacy protection from constrained healthcare devices to IoT cloud services. Cluster Computing, 22(1), 1611–1638.Google Scholar
  52. 52.
    Elmisery, A. M., Rho, S., & Botvich, D. (2016). A fog based middleware for automated compliance with OECD privacy principles in internet of healthcare things. IEEE Access, 4, 8418–8441.Google Scholar
  53. 53.
    Rajagopalan, A., Jagga, M., Kumari, A., & Ali, S. T. (2017). A DDoS prevention scheme for session resumption SEA architecture in healthcare IoT. In 2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT) (pp. 1–5). Piscataway, NJ: IEEE.Google Scholar
  54. 54.
    Chaudhry, J., Saleem, K., Islam, R., Selamat, A., Ahmad, M., & Valli, C. (2017). AZSPM: Autonomic zero-knowledge security provisioning model for medical control systems in fog computing environments. In 2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops) (pp. 121–127). Piscataway, NJ: IEEE.Google Scholar
  55. 55.
    Al Hamid, H. A., Rahman, S. M. M., Hossain, M. S., Almogren, A., & Alamri, A. (2017). A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access, 5, 22313–22328.Google Scholar
  56. 56.
    Vora, J., Nayyar, A., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., et al. (2018). BHEEM: A blockchain-based framework for securing electronic health records. In 2018 IEEE Globecom Workshops (GC Wkshps) (pp. 1–6). Piscataway, NJ: IEEE.Google Scholar
  57. 57.
    Liu, X., Deng, R. H., Yang, Y., Tran, H. N., & Zhong, S. (2018). Hybrid privacy-preserving clinical decision support system in fog–cloud computing. Future Generation Computer Systems, 78, 825–837.Google Scholar
  58. 58.
    Moosavi, S. R., Gia, T. N., Nigussie, E., Rahmani, A. M., Virtanen, S., Tenhunen, H., et al. (2016). End-to-end security scheme for mobility enabled healthcare Internet of Things. Future Generation Computer Systems, 64, 108–124.Google Scholar
  59. 59.
    Tanwar, S., Parekh, K., & Evans, R. (2020). Blockchain-based electronic healthcare record system for healthcare 4.0 applications. Journal of Information Security and Applications, 50, 102407.Google Scholar
  60. 60.
    Aazam, M., & Huh, E. N. (2015). Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. In 2015 IEEE 29th International Conference on Advanced Information Networking and Applications (pp. 687–694). Piscataway, NJ: IEEE.Google Scholar
  61. 61.
    Vora, J., DevMurari, P., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2018). Blind signatures based secured e-healthcare system. In 2018 International Conference on Computer, Information and Telecommunication Systems (CITS) (pp. 1–5). Piscataway, NJ: IEEE.Google Scholar
  62. 62.
    Gupta, R., Tanwar, S., Tyagi, S., Kumar, N., Obaidat, M. S., & Sadoun, B. (2019). HaBiTs: Blockchain-based telesurgery framework for healthcare 4.0. In 2019 International Conference on Computer, Information and Telecommunication Systems (CITS) (pp. 1–5). Piscataway, NJ: IEEE.Google Scholar
  63. 63.
    Tanwar, S., Vora, J., Kaneriya, S., Tyagi, S., Kumar, N., Sharma, V., et al. (2019). Human arthritis analysis in fog computing environment using Bayesian network classifier and thread protocol. IEEE Consumer Electronics Magazine, 9(1), 88–94.Google Scholar
  64. 64.
    Hossain, M., Islam, S. R., Ali, F., Kwak, K. S., & Hasan, R. (2018). An Internet of Things-based health prescription assistant and its security system design. Future Generation Computer Systems, 82, 422–439.Google Scholar
  65. 65.
    He, S., Cheng, B., Wang, H., Huang, Y., & Chen, J. (2017). Proactive personalized services through fog-cloud computing in large-scale IoT-based healthcare application. China Communications, 14(11), 1–16.Google Scholar

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Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Institute of TechnologyNirma UniversityAhmedabadIndia

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