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 is limited to K. We obtain closed form expressions 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 are model parameters. The parameters
are estimated by maximizing the log-likelihood function of the
measured average response time. Compared to other models,
our model is conceptually simple and it is easy to estimate
model parameters. The model has been validated through
measurements in our lab. The performance metrics predicted
by the model fit well to the experimental outcome.