References
- S. M. R. Islam, D. Kwak, M. D. H. Kabir, M. Hossain, and K.-S. Kwak, “The internet of things for health care: a comprehensive survey,” IEEE access, vol. 3, pp. 678–708, 2015.
- M. Rahmani et al., “Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach,” Futur. Gener. Comput. Syst., vol. 78, pp. 641–658, 2018.
- S. Tuli, N. Basumatary, and R. Buyya, “Edgelens: Deep learning-based object detection in integrated iot, fog and cloud computing environments,” in 2019 4th International Conference on Information Systems and Computer Networks (ISCON), 2019, pp. 496–502.
- S. S. Gill, R. C. Arya, G. S. Wander, and R. Buyya, “Fog-based smart healthcare as a big data and cloud service for heart patients using IoT,” in International Conference on Intelligent Data Communication Technologies and Internet of Things, 2018, pp. 1376–1383.
- S. He, B. Cheng, H. Wang, Y. Huang, and J. Chen, “Proactive personalized services through fog-cloud computing in largescale IoT-based healthcare application,” China Commun., vol. 14, no. 11, pp. 1–16, 2017.
- Abdullahi, S. Arif, and S. Hassan, “Ubiquitous shift with information centric network caching using fog computing,” in Computational intelligence in information systems, Springer, 2015, pp. 327–335.
- M. Satyanarayanan, “The emergence of edge computing,” Computer (Long. Beach. Calif)., vol. 50, no. 1, pp. 30–39, 2017.
- Goyal et al., “Seasonal variation in 24 h blood pressure profile in healthy adults-A prospective observational study,” J. Hum. Hypertens., vol. 33, no. 8, pp. 626–633, 2019
- A. Omala, A. S. Mbandu, K. D. Mutiria, C. Jin, and F. Li, “Provably secure heterogeneous access control scheme for wireless body area network,” Journal of Medical Systems, vol. 42, no. 6, p. 108, 2018.
- G. Gao, X. Peng, and L. Jin, “Efficient access control scheme with certificateless signcryption for wireless body area networks,” International Journal of Network Security, vol. 21, pp. 428–437, 2019.
- Ullah, A. Alomari, N. Ul Amin, M. A. Khan, and H. Khattak, “An energy efficient and formally secured certificate-based signcryption for wireless body area networks with the internet of things,” Electronics, vol. 8, no. 10, p. 1171, 2019.
- Iqbal, A. I. Umar, N. Amin, and A. Waheed, “Efficient and secure attribute-based heterogeneous online/offline signcryption for body sensor networks based on blockchain,” International Journal of Distributed Sensor Networks, vol. 15, no. 9, 2019.
- La, Q. D., Ngo, M. V., Dinh, T. Q., Quek, T. Q. S., & Shin, H. (2019). Enabling intelligence in fog computing to achieve energy and latency reduction. Journal of Digital Communications and Networks. Springer.
- Muniswamaiah, M., Agerwala, T., & Tappert, C. C. (2021). Fog Computing and the Internet of Things (IoT): A Review. In 2021 8th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2021 7th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom) (pp. 10-12). IEEE. https://doi.org/10.1109/CSCloud-EdgeCom52276.2021.00012
- Hazra, A., Rana, P., Adhikari, M., & Amgoth, T. (2023). Fog computing for next-generation Internet of Things: Fundamental, state-of-the-art and research challenges. Computer Science Review, 48, 100549. https://doi.org/10.1016/j.cosrev.2023.100549
- Bhatia, J., Italiya, K., Jadeja, K., Kumhar, M., Chauhan, U., Tanwar, S., Bhavsar, M., Sharma, R., Manea, D. L., Verdes, M., et al. (2023). An Overview of Fog Data Analytics for IoT Applications. Sensors, 23(1), 199. https://doi.org/10.3390/s23010199
- Kashyap, V., Kumar, A., Kumar, A., & Hu, Y.-C. (2022). A Systematic Survey on Fog and IoT Driven Healthcare: Open Challenges and Research Issues. Electronics, 11(17), 2668. https://doi.org/10.3390/electronics11172668
- Narayana, V.L. and Patibandla, R.S.M.L. (2021). An Efficient Fog-Based Model for Secured Data Communication. In Integration of Cloud Computing with Internet of Things (eds M. Mangla, S. Satpathy, B. Nayak and S.N. Mohanty). https://doi.org/10.1002/9781119769323.ch3
- Venkadesh, R., & Manojee, K. S. (2018). Examining the Effectiveness of Cloudlets in Mobile Computing. International Journal of Advanced Research in Engineering and Technology, 9(6), 274-280. https://doi.org/10.17605/OSF.IO/XC4K3
- Cuervo, E., Balasubramanian, A., Cho, D., Wolman, A., Saroiu, S., Chandra, R., & Bahl, P. (2010). MAUI: Making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (pp. 49-62). https://doi.org/10.1145/1814433.1814441
- Huang, H., Cai, Y., & Yu, H. (2016). Distributed-neuron-network based machine learning on smart-gateway network towards real-time indoor data analytics. In Proceedings of the 2016 Conference on Design, Automation & Test in Europe (pp. 720-725). EDA Consortium.
- Ngo, M. V., La, Q. D., Leong, D., & Quek, T. Q. S. (2017). User behavior driven MAC scheduling for body sensor networks. In Proceedings of IEEE HealthCom, Dalian, China (pp. 1-6).
- Kalpana, S., & Annadurai, C. (2022). Optimized cognitive learning model for energy efficient fog-BAN-IoT networks. Computer Systems Science & Engineering, 43(3), 1027-1040. https://doi.org/10.32604/csse.2022.024685
- Mary, S. A., & Malaisamy, M. (2021). Deep learning based energy efficient novel scheduling algorithms for body-fog-cloud in smart hospital. Journal of Ambient Intelligence and Humanized Computing, 12. https://doi.org/10.1007/s12652-020-02421-0