They suggest to consider as well the impact of the round trip times into the model in order to improve the accuracy of estimations. Based on their findings, Anton Riedl also proposes an extension of the processor sharing model to explicitly consider the round trip times and the impact of TCP slow start effect in [RPBP00]. These studies prove that the processor sharing model is an appropriate model for dimensioning the IP networks for elastic traffic. For elastic traffic, there has been also extensive research on developing detailed models for persistent TCP flows which are based on a very detailed view of TCP (such as in [OKM96, LM97]). They allow thorough performance investigations and as well provide good insight and understanding of TCP's behavior. However, due to their complexity they are not very practical for the purpose of network dimensioning. For network dimensioning a more macroscopic approach is essential. This is why the processor sharing model becomes very popular. It hides the details of the TCP protocol, requires only a few input parameters, and can be solved quickly. Overall, it provides a simple, efficient, yet powerful theoretical framework. 6.3 Dimensioning for Elastic Traffic 6.3.3 Processor Sharing Model for Elastic Traffic The Processor sharing (PS) model was originally developed to evaluate multi-tasking schemes on computers with a single processor [Kle76]. The computation resource is shared among several jobs by specifying time slots, during which the processing power is exclusively utilized by one of the jobs. Typically, the processor time is assigned in a fair round robin manner. If the time slots are set small enough, the serving of the individual jobs appears to be quasi-simultaneous. The time-sharing process, where the time slots are approaching zero, is denoted as processor sharing [Rie04]. In such systems, it can be assumed that all jobs are theoretically served simultaneously. A lot of work has been published, studying the characteristics and the performance of processor sharing sy