<p>With the advance in computer and network technologies, multimedia systems and Internet applications are becoming more popular. As broadband network is prevailing, more clients are able to watch streaming videos or to play multimedia data over the Internet in real-time. Consequently, there is an increasing demand in the Internet for streaming video systems. As the run-time environment of such applications tends to be dynamic, it is imperative to handle transient overloads effectively. The goal of this work is to develop an algorithm that would provide a robust and controlled behavior of the video system so that important data is delivered on time to the video clients. In order to address this problem, we propose a QoS-sensitive approach that is using the technique of imprecise computation and is based on the principle of tuning. Our algorithm is aimed to provide the best possible QoS to the clients in the current available network capacity. As an environment to work with we have used a video system called QMPEGv2. A set of experiments were carried out to evaluate the performance of the algorithm. Through experiments, we show that the system can adapt to dynamic changes in network conditions and provide almost always the best possible QoS to its clients. Guaranteeing a certain minimal QoS level to all clients is only possible when, in run time, an admission controller adjusts the number of clients admitted tothe system according to the capacity of the network and video servers.</p>

With the advance in computer and network technologies, multimedia systems and Internet applications are becoming more popular. As broadband network is prevailing, more clients are able to watch streaming videos or to play multimedia data over the Internet in real-time. Consequently, there is an increasing demand in the Internet for streaming video systems. As the run-time environment of such applications tends to be dynamic, it is imperative to handle transient overloads effectively. The goal of this work is to develop an algorithm that would provide a robust and controlled behavior of the video system so that important data is delivered on time to the video clients. In order to address this problem, we propose a QoS-sensitive approach that is using the technique of imprecise computation and is based on the principle of tuning. Our algorithm is aimed to provide the best possible QoS to the clients in the current available network capacity. As an environment to work with we have used a video system called QMPEGv2. A set of experiments were carried out to evaluate the performance of the algorithm. Through experiments, we show that the system can adapt to dynamic changes in network conditions and provide almost always the best possible QoS to its clients. Guaranteeing a certain minimal QoS level to all clients is only possible when, in run time, an admission controller adjusts the number of clients admitted tothe system according to the capacity of the network and video servers.

We propose an object-based multimedia model for specifying the QoS (quality of service) requirements, such as the maximum data-dropping rate or the maximum data-delay rate. We also present a resource allocation model, called the net-profit model, in which the satisfaction of user¡¦s QoS requirements is measured by the benefit earned by the system. Based on the net-profit model, the system is rewarded if it can allocate enough resources to a multimedia delivery request and fulfill the QoS requirements specified by the user. At the same time, the system is penalized if it cannot allocate enough resources to a multimedia delivery request. In this dissertation, we present our research in developing optimal solutions for multimedia stream delivery in bandwidth limited networks. To fulfill the QoS requirements, the resource, such as bandwidth, should be reserved in advance. Hence, we first investigate how to allocate a resource such that the QoS satisfaction is maximized, assuming that the QoS requirements are given a priori. The proposed optimal solution has significant improvement over the based line algorithm, EDF (Earliest Deadline First). Among all the optimal solutions found from the above problem, the net-profit may be distributed unevenly among the multimedia delivery requests. Furthermore, we tackle the fairness problem -- how to allocate a resource efficiently so that the difference of the net-profit between two requests is minimized over all the possible optimal solutions of the maximum total net-profit. A dynamic programming based algorithm is proposed to find all the possible optimal solutions and, in addition, three filters are conducted to improve the efficiency of the proposed algorithm. The experimental results show that the filters prune out unnecessary searches and improve the performance significantly, especially when the number of tasks increases. For some multimedia objects, they might need to be delivered in whole, indivisible, so we extend the proposed multimedia object-based model to indivisible objects. A dynamic programming based algorithm is presented to find an optimal solution of the delivery problem, where the total net-profit is maximized.