DApp monitoring data

Citation Author(s):
Ruyue
Xin
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

Submitted by Ruyue Xin on Sun, 02/27/2022 - 15:08