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DApp monitoring data
- Citation Author(s):
- Submitted by:
- Ruyue Xin
- Last updated:
- Sun, 02/27/2022 - 15:07
- DOI:
- 10.21227/jtkj-ke56
- License:
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Abstract
This dataset is collected from a running Decentralized Application (DApp). When the DApp receives transaction requests stably, we add system pressures with stress-ng, such as I/O pressure to inject anomalies manually. We increase disk pressure for 20 minutes every hour. We keep monitoring the DApp for 12 hours and collect data every 15 seconds, resulting in 3237 samples and 229 resource-related metrics for our experiments. In addition, an important metric that represents the number of transaction failures can be seen as the anomaly indicator of the DApp.
Instructions:
To use this dataset, you can simply read it with python pickle. The data includes more than 3k samples and more than 200 metrics.
Comments
First submission