Abstract
Wireless body area networks (WBANs) have become popular for providing real-time healthcare monitoring services. WBANs are an important subset of Cyber-physical systems (CPS). As the amount of sensing devices in such healthcare applications is growing rapidly, security, scalability, availability and privacy are a real challenge. Adoption of cloud computing is growing in the healthcare sector because it can provide high scalability while ensuring availability and affordable healthcare monitoring services. Serverless computing brings a new era to the design and deployment of event-driven applications in cloud computing. Serverless computing also helps the developer to build a large application using Function as a Service without thinking about the management and scalability of the infrastructure. The goal of this paper is to propose a dependable serverless architecture for WBAN applications. This architecture will improve the dependability of WBAN applications through ensuring scalability, availability, security and privacy by design, in addition to being cost-effective. This paper presents a detailed price comparison between two leading cloud service providers. Additionally, this paper reports on the findings from a case study which evaluated security, scalability and availability of the proposed architecture. This evaluation was conducted by load testing and rule-based intrusion detection.
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Acknowledgement
This work was supported with the financial support of the Science Foundation Ireland grant 13/RC/2094 and co-funded under the European Regional Development Fund through the Southern and Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie). Additionally, this work was partly funded by the DEIS H2020 project (Grant Agreement 732242).
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Paul, P.C., Loane, J., McCaffery, F., Regan, G. (2019). A Serverless Architecture for Wireless Body Area Network Applications. In: Papadopoulos, Y., Aslansefat, K., Katsaros, P., Bozzano, M. (eds) Model-Based Safety and Assessment. IMBSA 2019. Lecture Notes in Computer Science(), vol 11842. Springer, Cham. https://doi.org/10.1007/978-3-030-32872-6_16
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DOI: https://doi.org/10.1007/978-3-030-32872-6_16
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