Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework
- DOI
- 10.1186/s13677-024-00677-x
- Published
- 2024-06-04
- Container
- Journal of Cloud Computing
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13677-024-00677-x,
title = {Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework},
author = {Hongxia He and Xi Li and Peng Chen and Juan Chen and Ming Liu and Lei Wu},
year = {2024},
journal = {Journal of Cloud Computing},
doi = {10.1186/s13677-024-00677-x},
url = {https://doi.org/10.1186/s13677-024-00677-x}
}RIS
TY - JOUR TI - Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework AU - Hongxia He AU - Xi Li AU - Peng Chen AU - Juan Chen AU - Ming Liu AU - Lei Wu PY - 2024 JO - Journal of Cloud Computing DO - 10.1186/s13677-024-00677-x UR - https://doi.org/10.1186/s13677-024-00677-x ER -
APA
He, H., Li, X., Chen, P., Chen, J., Liu, M., & Wu, L. (2024). Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework. Journal of Cloud Computing. https://doi.org/10.1186/s13677-024-00677-x
Source records
- crossref · retrieved 2026-09-25T18:32:58.174Z