Runtime Prediction of Queued Behaviour
Service-based software architectures are often modeled with queues and queuing networks. Such models are useful for performance evaluation and design. They can also assist in runtime maintenance and administration, but, in this context, it is often far more valuable to be able to forecast how QoS characteristics are likely to evolve in the near future. This is particularly important in cases where systems can be adapted to counter QoS constraint violations: in such systems, given predictions of likely future QoS characteristics, pre-emptive adaptation strategies can be implemented.
This paper outlines an approach to runtime prediction of QoS characteristics of queued systems. Predictions are computed by applying ARIMA forecasting techniques to basic properties of a queued model, and then using the model to predict complex QoS characteristics. We outline how our methods integrate into our implementation framework for monitoring and pre-emptive adaptation of web service based systems.
KeywordsQueue Length Policy Language Adaptation Policy Adaptation Engine Average Queue Length
Unable to display preview. Download preview PDF.
- 3.Chan, K., Poernomo, I.: Model driven instrumentation for monitoring quality of service. In: Tenth IEEE International EDOC Enterprise Computing (submitted, 2006)Google Scholar
- 4.Chan, K., Poernomo, I., Schmidt, H.W., Jayaputera, J.: A Model-Oriented Framework for Runtime Monitoring of Nonfunctional Properties. In: Reussner, R., Mayer, J., Stafford, J.A., Overhage, S., Becker, S., Schroeder, P.J. (eds.) QoSA 2005 and SOQUA 2005. LNCS, vol. 3712, pp. 38–52. Springer, Heidelberg (2005)CrossRefGoogle Scholar
- 8.Dinda, P.A.: Online prediction of the running time of tasks. In: Joint International Conference on Measurement and Modeling of Computer Systems, pp. 336–337 (May 2001)Google Scholar
- 9.DMTF. Common information model (CIM) specification, version 2.2 (June 14, 1999), See: http://www.dmtf.org/standards/cim_schema_v22.php
- 11.Fortier, P.J., Michel, H.E.: Computer Systems Perfomance Evaluation and Prediction. Digital Press (2003)Google Scholar
- 14.Object Management Group. Uml profile for modeling quality of service and fault tolerance characteristics and mechanisms (2005), http://www.omg.org/cgi-bin/doc?ptc/2005-05-02
- 16.Januszewski, K.: Using UDDI at Run Time, Part II. Microsoft MSDN (accessed June 4, 2006), http://msdn.microsoft.com/library/default.asp?url=/library/en-us/dnuddi/html/runtimeuddi1.asp
- 18.Sharma, P.K., Loyall, J.P., Heineman, G.T., Schantz, R.E., Shapiro, R., Duzan, G.: Component-based dynamic qos adaptations in distributed real-time and embedded systems. In: International Symposium on Distributed Objects and Applications (DOA), Agia Napa, Cyprus, pp. 1208–1224 (October 25-29, 2004)Google Scholar