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Enhanced execution trace abstraction approach using social network analysis methods
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Datum
2020
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Gesellschaft für Informatik e.V.
Zusammenfassung
In this paper, we propose an improvement in system execution tracing by applying social network analysis techniques on the trace data. We perform a 3-step analysis: collection of trace data on operating system kernel; community analysis on the data; and PageRank algorithm within each community. The proposed analysis focused on the following problems: useless information contained in the data and the enormous size of the data. We propose two use cases: one on kernel trace filtering and the other on virtual machine clustering. Our evaluation shows that the proposed method provided a concise and more comprehensive view of the trace data. This can help shorten the time and assist in building infrastructural functions in analyzing system execution.