Optimizing Network Coding Algorithms for Multiple Applications.

Deviating from the archaic communication approach of treating information as a fluid moving through pipes, the concepts of Network Coding (NC) suggest that optimal throughput of a multicast network can be achieved by processing information at individual network nodes. However, existing challenges to harness the advantages of NC concepts for practical applications have prevented the development of NC into an effective solution to increase the performance of practical communication networks. In response, the research work presented in this thesis proposes cross-layer NC solutions to increase the network throughput of data multicast as well as video quality of video multicast applications. First, three algorithms are presented to improve the throughput of NC enabled networks by minimizing the NC coefficient vector overhead, optimizing the NC redundancy allocation and improving the robustness of NC against bursty packet losses. Considering the fact that majority of network traffic occupies video, rest of the proposed NC algorithms are content-aware and are optimized for both data and video multicast applications. A set of content and network-aware optimization algorithms, which allocate redundancies for NC considering content properties as well as the network status, are proposed to efficiently multicast data and video across content delivery networks. Furthermore content and channel-aware joint channel and network coding algorithms are proposed to efficiently multicast data and video across wireless networks. Finally, the possibilities of performing joint source and network coding are explored to increase the robustness of high volume video multicast applications. Extensive simulation studies indicate significant improvements with the proposed algorithms to increase the network throughput and video quality over related state-of-the-art solutions. Hence, it is envisaged that the proposed algorithms will contribute to the advancement of data and video multicast protocols in the future communication networks

S-RLNC based MAC Optimization for Multimedia Data Transmission over LTE/LTE-A Network

The high pace emergence in communication systems and associated demands has triggered academia-industries to achieve more efficient solution for Quality of Service (QoS) delivery for which recently introduced Long Term Evolution (LTE) or LTE-Advanced has been found as a promising solution. However, enabling QoS and Quality of Experience (QoE) delivery for multimedia data over LTE has always been a challenging task. QoS demands require reliable data transmission with minimum signalling overheads, computational complexity, minimum latency etc, for which classical Hybrid Automatic Repeat Request (HREQ) based LTE-MAC is not sufficient. To alleviate these issues, in this paper a novel and robust Multiple Generation Mixing (MGM) assisted Systematic Random Linear Network Coding (S-RLNC) model is developed to be used at the top of LTE MAC protocol stack for multimedia data transmission over LTE/LTE-A system. Our proposed model incorporated interleaving and coding approach along with MGM to ensure secure, resource efficient and reliable multiple data delivery over LTE systems. The simulation results reveal that our proposed S-RLNC-MGM based MAC can ensure QoS/QoE delivery over LTE systems for multimedia data communication

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

A low-energy rate-adaptive bit-interleaved passive optical network

Energy consumption of customer premises equipment (CPE) has become a serious issue in the new generations of time-division multiplexing passive optical networks, which operate at 10 Gb/s or higher. It is becoming a major factor in global network energy consumption, and it poses problems during emergencies when CPE is battery-operated. In this paper, a low-energy passive optical network (PON) that uses a novel bit-interleaving downstream protocol is proposed. The details about the network architecture, protocol, and the key enabling implementation aspects, including dynamic traffic interleaving, rate-adaptive descrambling of decimated traffic, and the design and implementation of a downsampling clock and data recovery circuit, are described. The proposed concept is shown to reduce the energy consumption for protocol processing by a factor of 30. A detailed analysis of the energy consumption in the CPE shows that the interleaving protocol reduces the total energy consumption of the CPE significantly in comparison to the standard 10 Gb/s PON CPE. Experimental results obtained from measurements on the implemented CPE prototype confirm that the CPE consumes significantly less energy than the standard 10 Gb/s PON CPE