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Open AccessArticle

Performance Testing of istSOS under High Load Scenarios

Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland, 6952 Cannobio, Switzerland
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ISPRS Int. J. Geo-Inf. 2019, 8(11), 467; https://doi.org/10.3390/ijgi8110467
Received: 2 September 2019 / Revised: 3 October 2019 / Accepted: 20 October 2019 / Published: 23 October 2019
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
In the last 20 years, a mainstream in Earth information and decision making has been drawn by the vision of the digital earth that calls for 3D representation, interoperability and modelling. In this context, the time dimension is essential but despite its importance, not many open standards and implementations are available. The Sensor Observation Service from the Open Geospatial Consortium is one of them and was specifically designed to collect, store and share timeseries of observations from sensors. To better understand the performance and limitation of one software implementation of this standard in real cases, this study executed a load testing of the istSOS application under a high load condition, characterized by a high number of concurrent users, in three cases mimicking existing monitoring networks. The results, in addition to providing reference values for future similar tests, show the general capacity of istSOS in meeting the INSPIRE quality of service requirements and in offering good performance with less than 500 concurrent users. When the number of concurrent users increases to 1000 and 2000, only 80% of the response times are below 30 seconds, performance that is unsatisfactory in most modern usages. View Full-Text
Keywords: open software; open standard; timeseries; monitoring; OGC; SOS open software; open standard; timeseries; monitoring; OGC; SOS
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MDPI and ACS Style

Cannata, M.; Antonovic, M.; Strigaro, D.; Cardoso, M. Performance Testing of istSOS under High Load Scenarios. ISPRS Int. J. Geo-Inf. 2019, 8, 467.

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  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.3515897
    Link: https://doi.org/10.5281/zenodo.3515897
    Description: IPython notebook with data used for the analysis and generation of plots
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