A Study of Web Services Performance Prediction: A Client's Perspective

The Web service (WS) paradigm is an emerging approach to building Web applications, in which software designers typically build new WSs by leveraging existing, third-party WSs. Understanding performance characteristics of third party WSs is critical to the overall system performance. Although such performance evaluation can be done through testing of third party WSs, it is quite an expensive process. This is especially the case when testing at high workloads, because performance degradations are likely to occur, which may render the WS under testing unusable during the tests' duration. Avoiding testing at high workloads by applying standard extrapolation approaches from data collected at low workloads (e.g., using regression analysis) results in a lack of accuracy. To address this challenge, in this paper, we propose a framework that utilizes the benefits of queueing models to guide the extrapolation process, while achieving accuracy in both regimes ¡V low and high workloads. Our extensive experiments show that our approach gives accurate results as compared to standard techniques (i.e., use of regression analysis alone).