Abstract As streaming techniques and wireless access networks become more widely deployed, a streaming multimedia connection with the "last mile" being a wireless network is becoming increasingly common. However, since current streaming techniques are primarily designed for wired networks, streaming multimedia applications can perform poorly in wireless networks. Recent link layer rate adaptation, contending traffic, and interference can link layer rate adaptation, contending traffic, and interference can significantly degrade the performance of streaming media applications. This performance degradation includes increased multimedia frame losses and lower image quality caused by packet loss, and multiple rebuffering events that stop the media playout. This dissertation presents the model, design, implementation and evaluation of an application layer solution for improving streaming multimedia application performance in IEEE 802.11 wireless networks by using enhanced bandwidth estimation techniques. The solution includes two parts: 1) a new Wireless Bandwidth estimation tool (WBest) designed for fast, non-intrusive, accurate estimation of available bandwidth in IEEE 802.11 networks, which can be used by streaming multimedia applications to improve the performance in wireless networks; 2) a Buffer and Rate Optimization for Streaming (BROS) algorithm using WBest to guide the streaming rate selection and initial buffer optimization. WBest and BROS are implemented and incorporated into an emulated streaming client-server system, Emulated Streaming (EmuS), in Linux and evaluated under a variety of wireless conditions. The evaluations show that with WBest and BROS, the performance of streaming multimedia applications in wireless networks can be significantly improved in terms of multimedia frame loss, rebuffer events and buffer delay.

This thesis evaluates software driven rate selection algorithms used in IEEE 802.11 wireless network interface cards. The motive of the bit-rate selection techniques is to optimize the throughput over the wireless network out of the many rates that are supported by the IEEE 802.11 link. The decision to switch from one rate to another with the changing link conditions to optimize the throughput is the primary focus of the bit-rate selection algorithms. Due to the uncertainty in the channel quality, it is a challenge to make the correct decision so as to minimize the wastage of network resources and achieve the highest throughput. This thesis also presents a novel learning bit-rate selection algorithm called the LeZiRate. LeZiRate uses the measurements of the quality of the signal received at the device to learn and predict the future quality of signal in near time. This thesis also presents a novel learning bit-rate selection algorithm called the LeZiRate. LeZiRate uses the measurements of the quality of the signal received at the device to learn and predict the future quality of signal in near time. Based on the prediction of channel condition it also selects the best bit-rate that would achieve the maximum throughput. LeZiRate does not monitor the network packets and therefore does not use any of the network resources. It monitors the signal quality received at the station and makes its decision based on that. It also makes the corrections to the prediction values by inducting the actual measurement of the signal quality on a real time basis so as to enable itself to make better predictions in the future. The LeZiRate algorithm monitors the signal quality and maps that to the received signal strength values, these values are quantized to map into a set of symbols. The frequency of occurrences of the string of these symbols is used to build a tree based on first order Markov model. It then selects the best bit-rate it believes would fetch the highest throughput. LeZiRate has a short setup and learning time to predict the first symbol. This thesis provides the simulation study of the LeZiRate algorithm and also presents simulation results of an existing bit-rate selection algorithm currently being used in the MADWiFi project for the multi-band Atheros wireless network interface cards. The simulation results show that LeZiRate is more sensitive to the changing link conditions of the wireless media although it does not use the network resources at all. The simulation study involved some measurements done through experimentation to collect realistic data and running the algorithms against that data.

Discusses the transport of real time data in WMNs as a challenging problem. The main cause of this problem is transport layer protocols. These protocols have traditionally been used successfully for wired networks. However, their raw implementation in wireless networks has proven to be inefficient, since wireless channels are characterized by a higher Bit Error Rate (BER), Packet Loss Rate (PLR), interference, bandwidth limitations and mobility when compared to wired network channels. Thus, for the efficient transport of real time video in WMNs, transport protocols need to be adapted to be adapted to wireless networks since they were not originally developed for this application.

Wireless networks is the fundamental component of next generation communication networks to provide users ubiquitous access. Due to the flexibility provided by wireless networks, users can access the network-based information and services anytime and anywhere. However, some emerging and popular multimedia applications, like Internet Protocol television (IPTV) and Multimedia Gaming, requiring high bandwidth and small delay, pose challenge for the last-mile wireless access network. Consequently, there is significant amount of research and development efforts in enhancing the performance of multimedia applications over wireless networks. This dissertation makes four important contributions towards that end. In Chapter 2, we study the various architectures, protocols and standards to support high quality video streaming over broadband mobile networks. We survey the most popular international video coding and compression standard ISO/IEC Moving Picture Experts Group-4 (MPEG-4) or ITU-T H.264. We also survey the next generation broadband mobile LTE (Long Term Evolution) network architecture and key technologies followed by video streaming delivery architectures and network protocols supporting video streaming over broadband mobile networks. Finally, we discuss possible future direction of video streaming in wireless networks. In Chapter 3, we propose an optimization algorithm to solve the key issue of bitrate switching in next generation HTTP-based adaptive video streaming. Our solution can provide the best possible viewing quality to users without playback interruption, which is reported as the biggest concern of on-line video streaming. The optimization algorithm is based on a specific streaming architecture and it can be easily integrated with other approaches and industry standards. Simulation results show that our optimization algorithm can determine the best video bitrate according to channel condition and buffered streams in local devices to provide viewers the best possible quality with least interruption. In Chapter 4, we propose a novel architecture and mechanism to delivery high quality video to users that use a wireless mesh access network. The novel mechanism consists of 1) a network route selection scheme which provides paths for multiple video streams with the least interference, called Minimum Interference Route Selection (MIROSE) and 2) an optimization algorithm that determines the compression rates depending on the network condition, called Network State Dependent Video Compression Rate (NSDVCR) algorithm. Simulation results show that our approach can provide significant improvement of video quality measured with Peak Signal-to-noise Ratio (PSNR) compared with standard routing protocols and default compression rates. In Chapter 5, we present a novel approach to collect multiple categories of data in a resource-limited wireless sensor network. In an advanced wireless sensor network capable of sensing and collecting multiple kinds of data, it is a challenging problem to efficiently and fairly collect various critical information when network has limited resources. We propose an optimization algorithm for the buffer management in the sensor node to provide higher event throughput, and maintain coverage fidelity when network is congested. Our detailed simulation analysis show that our proposed approach has significant performance improvement with respect to event throughput, fairness and the overall value of the information collected by the wireless sensor network. The dissertation proposes and validates a number of novel mechanisms and optimization algorithms to support the most challenging multimedia application namely, video, which has the dual requirements of high-bandwidth and small-delay, in various wireless networks. We first investigate the problem of providing high-quality video streaming in broadband mobile networks. We then enhance the video quality by 1) changing the video encoding and transmission techniques so as to be suitable for the wireless network; 2) designing a novel network architecture and protocol for video streaming; and 3) jointly altering the video compression and the network transport protocol.

Many emerging technologies such as video conferencing, video-on-demand, and digital libraries require the efficient delivery of compressed video streams. For applications that require the delivery of compressed stored multimedia streams, the a priori knowledge available about these compressed streams can aid in the allocation of server and network resources. By using a client-side buffer, the resource requirements from the server and network can be minimized. Buffering Techniques for Delivery of Compressed Video in Video-on-Demand Systems presents a comprehensive description of buffering techniques for the delivery of compressed, prerecorded multimedia data. While these techniques can be applied to any compressed data streams, this book focusses primarily on the delivery of video streams because of the large resource requirements that they can consume. The book first describes buffering techniques for the continuous playback of stored video sources. In particular, several bandwidth smoothing (or buffering) algorithms that are provably optimal under certain conditions are presented. To provide a well-rounded discussion, the book then describes extensions that aid in the ability to provide interactive delivery of video across networks. Specifically, reservation techniques that take into account interactive functions such as fast-forward and rewind are described. In addition, extensions to the bandwidth smoothing algorithms presented in the first few chapters are described. These algorithms are designed with interactive, continuous playback of stored video in mind and are also provably optimal under certain constraints. Buffering Techniques for Delivery of Compressed Video in Video-on-Demand Systems serves as an excellent resource for multimedia systems, networking and video-on-demand designers, and may be used as a text for advanced courses on the topic.