A Visualization Methodfor Cloud Service Networkswith Dual Hierarchical StructuresandMulti-device Attributes

Existing visualization methods for cloud service networks struggle to collaboratively present dual hierar-chical structures of spatial and logical deployments along with diverse device attributes, which adversely affects operational efficiency. This paper proposes a network simplification algorithm that utilizes node aggregations on equivalent node units to preserve network characteristics meanwhile reduce network scale. Then, a collaborative layout algorithm that integrates weighted Voronoi-based nested segmentation with a strong-boundary-constrained force-directed layout is designed to achieve the seamless presentation of dual hierarchical structures. Finally, a set of visual encodings and interactions are designed to depict device at-tributes. Experiments and case studies were conducted on six real-world cloud service networks of varying scales. The results demonstrate that the proposed method achieves superior performance across multiple aspects: in terms of algorithmic performance, the alarm aggregation rate remained at 0%, the average de-gree deviation ranged from 6.43% to 13.90%, and the node aggregation rate reached 89.38% to 94.93%; in terms of visual perception efficiency, the visual center index ranged from 0.86% to 0.91%, and the node overlap rate was controlled between 0% to 0.37%; regarding practical operational support, volunteers completed four tasks derived from reference real-world alarm analysis scenarios in an average time of 5.96 s to 8.12 s, achieving an accuracy of 95.00% to 100.00%, and the average scores of three Likert-scale evaluations of visualization effectiveness ranged from 4.1 to 4.4. All results outperform the comparative methods.