Name
Title | ||
|---|---|---|
Maximising the availability of an internet of medical things system using surrogate models and nature-inspired approaches |
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. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1504/IJGUC.2022.124381 | INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING |
Keywords | DocType | Volume |
internet of medical things, availability, surrogate models, nature-inspired approaches | Journal | 13 |
Issue | ISSN | Citations |
2-3 | 1741-847X | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guto Leoni Santos | 1 | 12 | 8.85 |
| Demis Gomes | 2 | 0 | 3.04 |
| Francisco Airton Silva | 3 | 2 | 6.45 |
| Patricia Takako Endo | 4 | 0 | 0.34 |
| Theo Lynn | 5 | 0 | 0.34 |