On the Scaling of Drone Imagery Platform Methodology Based on Container Technology


Phitchawat Lukkanathiti, Chantana Chantrapornchai, Journal of Information Processing Systems Vol. 20, No. 4, pp. 442-457, Aug. 2024  

https://doi.org/10.3745/JIPS.04.0313
Keywords: Cloud computing, Container Technology, Drone Imagery Processing, Infrastructure as Code, WebODM
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Abstract

The issues were studied of an open-source scaling drone imagery platform, called WebODM. It is known that processing drone images has a high demand for resources because of many preprocessing and post-processing steps involved in image loading, orthophoto, georeferencing, texturing, meshing, and other procedures. By default, WebODM allocates one node for processing. We explored methods to expand the platform's capability to handle many processing requests, which should be beneficial to platform designers. Our primary objective was to enhance WebODM's performance to support concurrent users through the use of container technology. We modified the original process to scale the task vertically and horizontally utilizing the Kubernetes cluster. The effectiveness of the scaling approaches enabled handling more concurrent users. The response time per active thread and the number of responses per second were measured. Compared to the original WebODM, our modified version sometimes had a longer response time by 1.9%. Nonetheless, the processing throughput was improved by up to 101% over the original WebODM’s with some differences in the drone image processing results. Finally, we discussed the integration with the infrastructure as code to automate the scaling is discussed.


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Cite this article
[APA Style]
Lukkanathiti, P. & Chantrapornchai, C. (2024). On the Scaling of Drone Imagery Platform Methodology Based on Container Technology. Journal of Information Processing Systems, 20(4), 442-457. DOI: 10.3745/JIPS.04.0313.

[IEEE Style]
P. Lukkanathiti and C. Chantrapornchai, "On the Scaling of Drone Imagery Platform Methodology Based on Container Technology," Journal of Information Processing Systems, vol. 20, no. 4, pp. 442-457, 2024. DOI: 10.3745/JIPS.04.0313.

[ACM Style]
Phitchawat Lukkanathiti and Chantana Chantrapornchai. 2024. On the Scaling of Drone Imagery Platform Methodology Based on Container Technology. Journal of Information Processing Systems, 20, 4, (2024), 442-457. DOI: 10.3745/JIPS.04.0313.