Title: Maximising the availability of an internet of medical things system using surrogate models and nature-inspired approaches

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

Addresses: Universidade Federal de Pernambuco (UFPE), Recife, Pernambuco, Brazil ' Universidade Federal de Pernambuco (UFPE), Recife, Pernambuco, Brazil ' Universidade Federal do Piaui (UFPI), Teresina, Piaui, Brazil ' Universidade de Pernambuco (UPE), Recife, Pernambuco, Brazil ' Business School, Dublin City University (DCU), Dublin, Ireland

Abstract: The emergence of new computing paradigms such as fog and edge computing provides the Internet of Things with needed connectivity and high availability. In the context of e-health systems, wearable sensors are being used to continuously collect information about our health, and forward it for processing by the Internet of Medical Things (IoMT). E-health systems are designed to assist subjects in real-time by providing them with a range of multimedia-based health services and personalised treatment with the promise of reducing the economic burden on health systems. Nonetheless, any service downtime, particularly in the case of emergency services, can lead to adverse outcomes and in the worst case, loss of life. In this paper, we use an interdisciplinary approach that combines stochastic models with surrogate-assisted optimisation algorithms to maximise e-health system availability considering the budget to acquire redundant components as a constraint, comparing three nature-inspired meta-heuristic optimisation algorithms.

Keywords: internet of medical things; availability; surrogate models; nature-inspired approaches.

DOI: 10.1504/IJGUC.2022.124381

International Journal of Grid and Utility Computing, 2022 Vol.13 No.2/3, pp.291 - 308

Received: 07 May 2020
Accepted: 18 Nov 2020
Published online: 26 Jul 2022 *

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