Monitoring and prediction of network performance

Analysis of network and application performance is traditionally based on mathematical models derived from first principles. Such models are usually complex, difficult to use, and do not exhibit satisfactory accuracy. This paper describes a new way of achieving high accuracy in predicting network performance. The new solution is built on a unique combination of network-component models and probabilistic analysis. The resulting model-based approach provides high fidelity for decision making in both monitoring and prediction modes. This paper discusses key features of the technique and illustrative results. Resulting capabilities are implemented in a system called NetPredictor^TM, which can monitor and predict quality of service (QoS) and compliance with service-level agreements (SLAs). It also empowers users to perform service-level management (SLM) and to make informed decisions about effects of contemplated changes in a network. Networks can be combinations of LANs, WANs, intranets, and the Internet