pacts, extensions on the basic processor sharing model have to be made in order to enhance the accuracy of estimations for the expected sojourn time and thus provide a more precise link dimensioning results. In section 6.3.7 a number of proposed extensions of the M/G/R-PS model by the author for the dimensioning of the lub will be presented in detail. 6.3.4 Application of M/G/R-PS Model for Dimensioning lub Interface This section introduces the analytical model for the dimensioning of the lub link in the UMTS radio access networks. The analytical model is based on the processor sharing model. Figure 6.16 presents the system model of the lub interface at flow or connection level. The elastic traffic is generated by downloading Internet objects, e.g. file transfers or downloading web objects. Each Node B serves a number of mobile users (UEs), who are transmitting elastic traffic over TCP connections. The TCP connections are established between the UEs and their requesting data servers located in the external networks (e.g. Internet). It is assumed 6.3 Dimensioning for Elastic Traffic that each elastic traffic flow is related to a single data transfer process and the sojourn time represents the expected transfer time. When considering the World Wide Web as the main application, one traffic flow can also represent a number of different web objects downloaded from the same server. Since HTTP/1.1 [FGM*99] allows the download of several web objects within one TCP connection, individual transmission processes can be considered as one transfer process. The size of the transferred data is equal to the sum of the individual object lengths. Measurements of web traffic have shown that the amount of transmitted data shows heavy-tail characteristics [Cha00]. This means that most of the transfer processes are short while there are some extremely long ones. Thus, it can be assumed that the downloaded Internet object sizes are generally distributed, e.g. modeled by a hyper-exponential or Pareto distribution. Furthermore, since eac