Nguyen, Hoa, Zhu, Shaoshu and Liu, Mingming ORCID: 0000-0002-8988-2104 (2022) A Survey on graph neural networks for microservice-based cloud applications. Sensors, 22 (23). ISSN 1424-8220
Abstract
Graph neural networks (GNNs) have achieved great success in many research areas
ranging from traffic to computer vision. With increased interest in cloud-native applications, GNNs
are increasingly being investigated to address various challenges in microservice architecture from
prototype design to large-scale service deployment. To appreciate the big picture of this emerging
trend, we provide a comprehensive review of recent studies leveraging GNNs for microservice-based
applications. To begin, we identify the key areas in which GNNs are applied, and then we review in
detail how GNNs can be designed to address the challenges in specific areas found in the literature.
Finally, we outline potential research directions where GNN-based solutions can be further applied.
Our research shows the popularity of leveraging convolutional graph neural networks (ConGNNs)
for microservice-based applications in the current design of cloud systems and the emerging area of
adopting spatio-temporal graph neural networks (STGNNs) and dynamic graph neural networks
(DGNNs) for more advanced studies
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | anomaly detection; graph neural networks; microservices; resource scheduling; software decomposition |
Subjects: | Computer Science > Artificial intelligence Computer Science > Computer software Computer Science > Machine learning Engineering > Systems engineering |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Initiatives and Centres > INSIGHT Centre for Data Analytics |
Publisher: | MDPI |
Official URL: | https://dx.doi.org/10.3390/s22239492 |
Copyright Information: | © 2022 The Authors. |
Funders: | SFI/12/RC/2289_P2, Huawei Ireland Research Centre |
ID Code: | 27946 |
Deposited On: | 15 Dec 2022 12:27 by Mingming Liu . Last Modified 14 Mar 2023 14:41 |
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