Enhancing the quality of video streaming over unreliable wireless networks
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Real-time video transmission over unreliable wireless networks remains a serious challenge due to bandwidth limitation and sensitive nature of video bitstreams generated by today’s complex video encoders, e.g., High Efficiency Video Coding (HEVC/H.265). These compressed video bitsreams face packet-drop problem when transmitted over unreliable wireless networks. The effect of packet-drop on the received video quality can be minimised in two ways 1) increasing Quality of Service (QoS) by adopting efficient routing schemes between source and destination, and 2) maintaining video quality at receiver’s side by applying smart and real-time-based Error Concealment (EC) techniques. The QoS refers to the capability of a transmission network to provide better service to selected network traffic. It is a generic term and can be applied to any data transmission network. The term video quality refers to perceived video degradation and is compared to the original video. In this dissertation, we explore the above mentioned two ways and propose a comprehensive solution for real-time video transmission over unreliable networks with the contributions as follows. 1. An efficient, lightweight and real-time EC algorithm is proposed to conceal the missing/lost video frames in H.265 encoded HD videos. The EC algorithm is based on threshold-based distributed Motion Estimation (ME) scheme and utilises only two video frames to estimate the missing one, thus eliminating the need for a large buffer and processing of a bundle of video frames to estimate the missing one. 2. Scalable video coding produces multiple interrelated bitstreams of a single video with different bitrates. For scalable bitstreams, we propose a lightweight and real-time EC algorithm to cover up the effects of missing/lost video frames. Due to complicated nature of scalable video bitstreams, our proposed EC algorithm utilises three previously processed video frames along with their master video frames to perform threshold-based distributed ME to estimate the missing video frames in enhancement layer. 3. We propose a feed-back-based on-demand multipath routing scheme over a multi-hop Wireless Multimedia Sensor Network (WMSN) to ensure the QoS. The feedback helps in deciding the optimum path between sources and destinations and reduces the Packets Loss Ratio (PLR) during the transmissions. On-demand connection assists in saving the available network resources while multipath routing aids in maintaining the connection between sources and destinations. The proposed research makes notable contributions to designing a QoS-supported HD video streaming paradigm to deliver HD videos over unreliable networks and to maintain the received video quality on resource-constrained mobile terminals.
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