ProEva: runtime proactive performance evaluation based on continuous-time markov chains

Conference paper


Su, G., Chen, T., Feng, Y. and Rosenblum, D. 2017. ProEva: runtime proactive performance evaluation based on continuous-time markov chains. 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). Buenos Aires, Argentina 20 - 28 May 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 484-495 https://doi.org/10.1109/ICSE.2017.51
TypeConference paper
TitleProEva: runtime proactive performance evaluation based on continuous-time markov chains
AuthorsSu, G., Chen, T., Feng, Y. and Rosenblum, D.
Abstract

Software systems, especially service-based software systems, need to guarantee runtime performance. If their performance is degraded, some reconfiguration countermeasures should be taken. However, there is usually some latency before the countermeasures take effect. It is thus important not only to monitor the current system status passively but also to predict its future performance proactively. Continuous-time Markov chains (CTMCs) are suitable models to analyze time-bounded performance metrics (e.g., how likely a performance degradation may occur within some future period). One challenge to harness CTMCs is the measurement of model parameters (i.e., transition rates) in CTMCs at runtime. As these parameters may be updated by the system or environment frequently, it is difficult for the model builder to provide precise parameter values. In this paper, we present a framework called ProEva, which extends the conventional technique of time-bounded CTMC model checking by admitting imprecise, interval-valued estimates for transition rates. The core method of ProEva computes asymptotic expressions and bounds for the imprecise model checking output. We also present an evaluation of accuracy and computational overhead for ProEva.

Research GroupFoundations of Computing group
LanguageEnglish
Conference2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)
Page range484-495
ISSN1558-1225
ISBN
Hardcover9781538638682
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication dates
Print20 May 2017
Online20 Jul 2017
Publication process dates
Deposited15 Jun 2017
Accepted12 Dec 2016
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1109/ICSE.2017.51
Book titleICSE '17 Proceedings of the 39th International Conference on Software Engineering
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