M.Ing. / Previous research have entailed developing various network traffic models which describe network traffic behaviour, but no model describes differential traffic treatment to such an extent to be able to relate the impact different rates have on the various traffic classes. The main reason for this being the amount of parameters that needs to be taken into consideration. Previous research performed in this field, analysed certain schedulers according to fixed parameters, thus having a very limited results base. No detailed comparison of these schedulers behaviour in a Differentiated Services (DiffServ) environment is available since the parameters under which their analysis were performed are different. A first objective entailed performing a thorough literature survey concerning DiffSery to summarize the research material that is available. This gives us as well as the reader a foundation to start any future research and the means to make good use of this information. Secondly, a DiffSery module was ported from an old version of Ns-2 which was developed for an older Linux kernel and GCC version; to the newest available. Ns-2 was also limited in respects to traffic generation. We developed a traffic generator that generates traffic according to a certain statistical distribution. This generation is performed according to packet size since distributions according to arrival time was partially implemented already. Our aim is to provide an in depth study regarding the performance of the various schedulers in the network and the effect various network parameters have on them. Since no real-network trace data is available, we resort to computer simulations. With Ns-2, we implement four different standardized perhop-behaviours (PHBs), namely expedited forwarding (EF), assured forwarding (AF1, AF2) and besteffort (BE). The evaluation focuses mainly on the EF PHB in regards to the other PHBs. The priority queuing (PQ), start-time fair queuing (SFQ), self-clocked fair queuing (SCFQ), weighted fair queuing (WFQ), worst-case weighted fair queuing plus (WF2Q+) and low latency queuing (LLQ) scheduling mechanisms are analysed to find their performance in relation to EF traffic and BE traffic. The QoS metrics that are focused on are: one-way delay (OWD), inter-packet delay variation (IPDV) and packet loss. We used Analysis of Variance (ANOVA) to analyse the impact of the various DiffSery node configuration parameters such as rates, packets sizes, schedulers and queue weights have on the output QoS metrics mentioned previously. Regression is then used to explain the relationship between several of these factors and metrics.