Document Type
Conference Proceeding
Date of Original Version
2017
Abstract
The smart health paradigms employ Internet-connected wearables for telemonitoring, diagnosis for providing inexpensive healthcare solutions. Fog computing reduces latency and increases throughput by processing data near the body sensor network. In this paper, we proposed a secure service-orientated edge computing architecture that is validated on recently released public dataset. Results and discussions support the applicability of proposed architecture for smart health applications. We proposed SoA-Fog i.e. a three-tier secure framework for efficient management of health data using fog devices. It discuss the security aspects in client layer, fog layer and the cloud layer. We design the prototype by using win-win spiral model with use case and sequence diagram. Overlay analysis was performed using proposed framework on malaria vector borne disease positive maps of Maharastra state in India from 2011 to 2014. The mobile clients were taken as test case. We performed comparative analysis between proposed secure fog framework and state-of-the art cloud-based framework.
Citation/Publisher Attribution
Barik, R. B., Dubey, H., & Mankodiya, K. (2017, November 14-16). SOA-FOG: Secure service-oriented edge computing architecture for smart health big data analytics. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Montreal, QC, Canada. doi: 10.1109/GlobalSIP.2017.8308688
Available at: http://dx.doi.org/10.1109/GlobalSIP.2017.8308688
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