Use of model calibration to achieve high accuracy in analysis of computer networks
A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.
- Research Organization:
- NetPredict, Inc., Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- FG03-98ER82626
- Assignee:
- NetPredict, Inc. (Menlo Park, CA)
- Patent Number(s):
- 6,735,553
- Application Number:
- 10/031,751
- OSTI ID:
- 1174845
- Country of Publication:
- United States
- Language:
- English
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