A Visualization Method for Cloud Service Networks with Dual Hierarchical Structures and Multi-Device Attributes

Existing visualization methods for cloud service networks struggle to collaboratively present dual hierarchical 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 reducing 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 attributes. 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 degree deviation ranged from 6.43% to 13.90%, and the node simplified 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.