In this dissertation, we present performance prediction models for rate-based and window¡Vbased flow control mechanisms. For rate-based flow control, such as in ATM network, we derive two analytical models to predict the ACR rates for congestion-free and congestion networks, respectively. To coordinate the cooperative problems of TCP over ATM networks, we propose a new algorithm to monitor the states of ATM switches and adjust TCP congestion window size based on RM cells. For window-based flow control mechanisms, such as in TCP-Reno and TCP-SACK, we respectively present analytical models to systematically capture the characteristics of multiple consecutive packet losses in TCP windows. Through fast retransmission, the lost packets may or may not be recovered. Thus, we present upper bound analyses for slow start and congestion avoidance phases to study the effects of multiple packet losses on TCP performance. Above the proposed upper bounds, the lost packets may not be successfully recovered through fast retransmission. Finally, we develop a model to study the TCP performance in terms of throughput degradation resulted from multiple consecutive packet losses. The analytical results from the throughput degradation model are validated through OPNET simulation.

Background: In the recent years, the focus of research has shifted to Quality of Experience(QoE) to maintain the user satisfaction levels and fulfill their expectations of the serviceoffered. Numerous work has been established in finding the relationship between the networklayer and QoE. But, it is fact that the transport layer is much closer to the end-user than thenetwork layer in the TCP/IP communication protocol suite. Thus, any changes in the degreeof satisfaction or degree of annoyance are directly reflected onto transport layer than on thenetwork layer. So, it becomes more significant to study the behavior of user satisfaction inrelation to transport layer than the network layer. Objectives: This research is to relate the behavior of TCP to QoE. The main considerations tobridge the gap between them are: (a) Analyzing the effects of using different versions of TCPon server and client side, (b) Monitoring and analyzing the intensity of TCP traffic in thereverse direction and (c) Investigating TCP control flags from client to server. Methods: QoE related parameters used in this research are: (a) Quality of video i.e., MOS, (b)Degree of disturbance caused by initial delay, (c) Degree of disturbance caused by jerkinessand (d) Degree of disturbance caused by freezes. Effects of network impairments like delay,jitter and packet loss are considered in this research. NetEm is used as the traffic emulationsoftware to shape the traffic. The packet capture analysis of traffic exchange is implementedusing tcpdump. Results and Conclusions: The aim of this research is to provide a passive-estimation methodto assess the user perceived performance. The results of this research provide valuablecontribution to service providers/operators to note the early warning signals from TCP reversetraffic to evaluate the decrease of user satisfaction level and try to cope or/and recover fromimpairments in the network. This research also provides a scope for future researchers toinvestigate other protocols both in transport and application layers.

In order to easily send data between two end elements without congestion, methods that suitably control flow of date and evaluate possible overload state are necessary. One such method is to control the data flow directly on the transport layer. This layer offers a range of mechanisms dedicated to deal with this issue. The aim of this paper is divided into three parts. The first part describes the integration of transport layer TCP/IP model, and the ability to process TCP data stream. The second part describes methods to manage congestion, their integration by usage environment. It mainly focuses on methods of TCP Reno and TCP Vegas. Their simulation and analysis on transmission the data stream stream. The third part deals with the analysis in detail of TCP Vegas. Analyzes possible parameters for alpha a beta within the TCP Vegas, and a combination of TCP Vegas and TCP Reno.