Adaptive Monitoring for Continuous Performance Model Integration: Unterschied zwischen den Versionen

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|betreuer=Manar Mazkatli
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|termin=Institutsseminar/2019-07-12
|termin=Institutsseminar/2019-07-12
|kurzfassung=TBD
|kurzfassung=Performance Models (PMs) can be used to predict software performance and evaluate the alternatives at the design stage. Building such models manually is a time consuming and not suitable for agile development process where quick releases have to be generated in short cycles. Existing approaches that extract PMs automatically based on reverse-engineering and/or measurement techniques require to monitor and analyze the whole system after each iteration, which will cause a high monitoring overhead.
 
The Continuous Integration of Performance Models (CIPM) approach address this problem by updating the PMs and calibrate it incrementally based on the adaptive monitoring of the changed parts of code.
In this work we introduced an approach "Adaptive Monitoring for Performance Model Integration”, which instruments automatically only the changed parts of the source code using specific pre-defined probes types.  Then it monitors the system adaptively. The resulting measurements are used by CIPM to estimate PM parameters incrementally.
The evaluation confirmed that our approach can reduce the monitoring overhead to 50%.
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Version vom 8. Juli 2019, 23:58 Uhr

Vortragende(r) Noureddine Dahmane
Vortragstyp Masterarbeit
Betreuer(in) Manar Mazkatli
Termin Fr 12. Juli 2019
Vortragssprache
Vortragsmodus
Kurzfassung Performance Models (PMs) can be used to predict software performance and evaluate the alternatives at the design stage. Building such models manually is a time consuming and not suitable for agile development process where quick releases have to be generated in short cycles. Existing approaches that extract PMs automatically based on reverse-engineering and/or measurement techniques require to monitor and analyze the whole system after each iteration, which will cause a high monitoring overhead.

The Continuous Integration of Performance Models (CIPM) approach address this problem by updating the PMs and calibrate it incrementally based on the adaptive monitoring of the changed parts of code. In this work we introduced an approach "Adaptive Monitoring for Performance Model Integration”, which instruments automatically only the changed parts of the source code using specific pre-defined probes types. Then it monitors the system adaptively. The resulting measurements are used by CIPM to estimate PM parameters incrementally. The evaluation confirmed that our approach can reduce the monitoring overhead to 50%.