Web server performance modeling using an M/G/1/K*PS queue

Performance modeling is an important topic in capacity planning and overload control for web servers. We present an M/G/1/K*PS queueing model of a web server. The arrival process of HTTP requests is assumed to be Poissonian and the service discipline is processor sharing. The total number of requests that can be processed at one time was limited to K. Closed form expressions were obtained for web server performance metrics such as average response time, throughput and blocking probability. The average of the service time requirement and the limit of the number of requests being served were model parameters. The parameters were estimated by maximizing the log-likelihood function of the measured average response time. Compared to other models, this model is conceptually simple and it is easy to estimate model parameters. The model had been validated through lab measurements. The performance metrics predicted by the model fit well to the experimental outcome.