Using observation ageing to improve Markovian model learning in QoS engineering

Calinescu, Radu, Johnson, Kenneth and Rafiq, Yasmin (2011). Using observation ageing to improve Markovian model learning in QoS engineering. IN: UNSPECIFIED New York, NY (US): ACM.


Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.

Publication DOI:
Divisions: Engineering & Applied Sciences > Computer science
Event Title: 2nd Joint WOSP/SIPEW International Conference on Performance Engineering
Event Type: Other
Event Dates: 2011-03-14 - 2011-03-16
Uncontrolled Keywords: Algorithms,Measurement,Reliability,Theory,Computer Science Applications,Software
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Published Date: 2011-03-14
Authors: Calinescu, Radu
Johnson, Kenneth
Rafiq, Yasmin


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