The appearance of Voice over IP (VoIP) revolutionized the telecommunications word, this technology delivers voice communications over the internet protocol (IP) networks instead of the public switched telephone network (PSTN), calls can be made between two VoIP phones as well as between a VoIP phone and an analog phone connected to a VoIP adapter [1]. The use of this technology gives access to more communication options compared to the conventional telephony but the users face different problems, mostly connectivity and performance issues related to different factors such as latency and jitter [2], these factors affect directly the call quality and can result in choppy voice, echoes, or even in a call failure. The main objective of this work was to create a tool for automatic analysis and evaluation from packet traces, identify connectivity and performance issues, reconstruct the audio streams and estimate the call quality. The results of this work showed that the objectives sated above are met, where a tool that automatically analyzes VoIP calls is created, this tool takes non encrypted pcap files as input and returns a list of calls with different parameters related to connectivity and performance such as delay and jitter, it does as well reconstruct the audio of every VoIP stream and plots the waveform and spectrum of the reconstructed audio for evaluation purposes.

Quality of Service (QoS) is the ability to guarantee that data sent across a network will be recieved by the desination within some constraints. For many advanced applications, such as real-time multimedia QoS is determined by four parameters--end-to-end delay, delay jitter, available bandwidth or throughput, and packet drop or loss rate. It is interesting to study and be able to predict the behavior of end-to-end packet delays in a Wide area network (WAN) because it directly a??ects the QoS of real-time distributed applications. In the current work a time-series representation of end-to-end packet delay dynamics transported over standard IP networks has been considered. As it is of interest to model the open loop delay dynamics of an IP WAN, the UDP is used for transport purposes. This research aims at developing models for single-step-ahead and multi-step-ahead prediction of moving average, one-way end-to-end delays in standard IP WAN??s. The data used in this research has been obtained from simulations performed using the widely used simulator ns-2. Simulation conditions have been tuned to enable some matching of the end-to-end delay profiles with real traffic data. This has been accomplished through the use of delay autocorrelation profiles. The linear system identification models Auto-Regressive eXogenous (AR) and Auto-Regressive Moving Average with eXtra / eXternal (ARMA) and non-linear models like the Feedforwad Multi-layer Perceptron (FMLP) have been found to perform accurate single-step-ahead predictions under varying conditions of cross-traffic flow and source send rates. However as expected, as the multi-step-ahead prediction horizon is increased, the models do not perform as accurately as the single-step-ahead prediction models. Acceptable multi-step-ahead predictions for up to 500 msec horizon have been obtained.