A NEW CLOUD-EDGE-TERMINAL RESOURCES COLLABORATIVE SCHEDULING FRAMEWORK FOR MULTI-LEVEL VISUALIZATION TASKS OF LARGE-SCALE SPATIO-TEMPORAL DATA

To address the multi-modal spatio-temporal data efficient scheduling problem of the diverse and highly concurrent visualization applications in cloud-edge-terminal environment, this paper systematically studies the cloud-edge-terminal integrated scheduling model of multi-level visualization tasks of...

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Published inInternational archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XLIII-B4-2020; pp. 477 - 483
Main Authors Li, X. M., Wang, W. X., Tang, S. J., Xia, J. Z., Zhao, Z. G., Li, Y., Zheng, Y., Guo, R. Z.
Format Journal Article Conference Proceeding
LanguageEnglish
Published Gottingen Copernicus GmbH 25.08.2020
Copernicus Publications
Subjects
Cloud computing
Collaboration
Construction
Construction management
Data
Mapping
Optimization
Prototypes
Quality assessment
Resource scheduling
Scheduling
Scientific visualization
Spatiotemporal data
Storage
Task scheduling
Visualization
Workflow
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Summary:To address the multi-modal spatio-temporal data efficient scheduling problem of the diverse and highly concurrent visualization applications in cloud-edge-terminal environment, this paper systematically studies the cloud-edge-terminal integrated scheduling model of multi-level visualization tasks of multi-modal spatio-temporal data. By accurately defining the hierarchical semantic mapping relationship between the diverse visual application requirements of different terminals and scheduling tasks, we propose a multi-level task-driven cloud-edge-terminal multi-granularity storage-computing-rendering resource collaborative scheduling method. Based on the workflow, the flexible allocation strategy of cloud-edge-terminal scheduling service chain that consider the characteristics of spatio-temporal task is constructed. Finally, we established a cloud-edge-terminal scheduling adaptive optimization mechanism based on the service quality evaluation model, and developed a prototype system. Experiments are conducted with the urban construction and construction management, the results show that the new method breaks through the bottleneck of traditional spatio-temporal data visualization scheduling, and it can provide theoretical and methodological support for the visualization and scheduling of spatio-temporal big data.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLIII-B4-2020-477-2020