Response times in client-server systems

Response time is the key performance measure in on-line transaction processing systems and other client-server architectures. Not only is it important to achieve a low average value and correspondingly high throughput, but response time should also be fairly consistent in order to provide a good quality of service. We develop a new algorithm for computing the probability density function of response times in Markovian models of client-server systems. We model the clients and servers by central server queueing networks and obtain response time densities as simple functions of time under independence assumptions that are shown to hold asymptotically as network size increases. The communication network is modelled as a single server queue with mean service time determined by its operational characteristics. We consider an Ethernet and construct a new model, of interest in its own right, that captures details not modelled hitherto. This model is validated against simulation and shows good agreement up to moderate utilisations, the normal operating environment for Ethernets. The whole client-server model is implemented in the Metron Athene Client-Server capacity planning tool and sample runs are examined.