Name
Title | ||
|---|---|---|
Integrated estimation and tracking of performance model parameters with autoregressive trends |
Abstract | ||
|---|---|---|
Adaptive management of a software service system can take advantage of a performance model which can predict the effect of proposed changes, before they are deployed. As the system varies over time the model parameters can be tracked by an estimator such as a Kalman Filter, so that decisions can be updated. The filter is valuable when parameters are 'hidden' and cannot be directly measured without excessive cost (as is usually the case for the CPU time of a service). Because there may be significant delays in some management control actions (especially in deploying a new replica of a service), it is also important to be able to predict the changes ahead somewhat in time, that is, to predict the trends. The trend predictor itself needs to be estimated from observed trends in the model parameters. This work uses an autoregressive model for trend prediction and integrates it with the parameter estimator, in a single Kalman Filter, using auxiliary states for the parameter evolution process. This paper describes how the trend model is constructed, and evaluates its effectiveness. It compares the overall performance predictions to a simpler trend predictor using linear extrapolation of the fitted parameter time-series, which turns out to be almost as good. The approach is validated on a real system running a benchmark web application. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1958746.1958772 | ICPE |
Keywords | Field | DocType |
trend predictor,model parameter,performance model parameter,trend model,trend prediction,observed trend,integrated estimation,simpler trend predictor,cpu time,autoregressive model,autoregressive trend,performance model,fitted parameter time-series,measurements,resource allocation,job scheduling | Autoregressive model,Data mining,Central processing unit,Mathematical optimization,Computer science,Kalman filter,Capacity planning,Control engineering,Resource allocation,Extrapolation,Job scheduler,Estimator | Conference |
Citations | PageRank | References |
15 | 0.69 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Zheng | 1 | 209 | 11.66 |
| Marin Litoiu | 2 | 2147 | 128.80 |
| Murray Woodside | 3 | 1215 | 81.20 |