Title: The internet of things for healthcare: optimising e-health system availability in the fog and cloud

Authors: Guto Leoni Santos; Demis Gomes; Judith Kelner; Djamel Sadok; Francisco Airton Silva; Patricia Takako Endo; Theo Lynn

Addresses: Universidade Federal de Pernambuco, Av. Prof. Moraes Rego, 1235 – Cidade Universitária, Recife, Pernambuco, Brazil ' Universidade Federal de Pernambuco, Av. Prof. Moraes Rego, 1235 – Cidade Universitária, Recife, Pernambuco, Brazil ' Universidade Federal de Pernambuco, Av. Prof. Moraes Rego, 1235 – Cidade Universitária, Recife, Pernambuco, Brazil ' Universidade Federal de Pernambuco, Av. Prof. Moraes Rego, 1235 – Cidade Universitária, Recife, Pernambuco, Brazil ' Universidade Federal do Piaui, Campus Universitário Ministro Petrônio Portella, s/n – Ininga, Teresina, Piauí, Brazil ' Universidade de Pernambuco, Av. Gov. Agamenon Magalhães – Santo Amaro, Recife, Pernambuco, Brazil ' Irish Institute of Digital Business, Dublin City University, Dublin, Ireland

Abstract: E-health systems can be used to monitor people in real-time, offering a range of multimedia-based health services, at the same time reducing the cost since cheaper devices can be used to compose it. However, any downtime, mainly in the case of critical health services, can result in patient health problems and in the worst case, loss of life. In this paper, we use an interdisciplinary approach combining stochastic models with optimisation algorithms to analyse how failures impact e-health monitoring system availability. We propose surrogate models to estimate the availability of e-health monitoring systems that rely on edge, fog, and cloud infrastructures. Then, we apply a multi-objective optimisation algorithm, NSGA-II, to improve system availability considering component costs as constraint. Results suggest that replacing components with more reliable ones is more effective in improving the availability of an e-health monitoring system than adding more redundant components.

Keywords: availability; cloud computing; edge computing; e-health systems; healthcare; fog computing; internet of things; IoT; optimisation algorithms; stochastic models; surrogate models.

DOI: 10.1504/IJCSE.2020.10028625

International Journal of Computational Science and Engineering, 2020 Vol.21 No.4, pp.615 - 628

Received: 03 Jan 2019
Accepted: 17 Apr 2019

Published online: 24 Apr 2020 *

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