A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video streaming, it may also cause a video bitrate oscillation. So the video buffer structure is adjusted by adding two thresholds as operating points for overflow and underflow states to filter the impact of throughput fluctuation on video buffer occupancy level. Then a bandwidth prediction algorithm is proposed for enhancing the performance of video bitrate adaptation. This algorithm's work depends on the current video buffer level, video bitrate of the previous segment, and iterative throughput measurements to predict the best video bitrate for the next segment. Simulation results show that reserving a bandwidth margin is better in adapting the video bitrate under bandwidth variation and then reducing the risk of video playback freezing. Simulation results proved that the playback freezing happens two times: firstly, when there is no bandwidth margin used and secondly, when the bandwidth margin is high while smooth video bitrate is obtained with moderate value. The proposed scheme is compared with other two schemes such as smoothed throughput rate (STR) and Buffer Based Rate (BBR) in terms of prediction error, QoE preferences, buffer size, and startup delay time, then the proposed scheme outperforms these schemes in attaining smooth video bitrates and continuous video playback.
The most popular medium that being used by people on the internet nowadays is video streaming. Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the
... Show MoreThis work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different video
... Show MoreA new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever
... Show MoreMPEG-DASH is an adaptive bitrate streaming technology that divides video content into small HTTP-objects file segments with different bitrates. With live UHD video streaming latency is the most important problem. In this paper, creating a low-delay streaming system using HTTP 2.0. Based on the network condition the proposed system adaptively determine the bitrate of segments. The video is coded using a layered H.265/HEVC compression standard, then is tested to investigate the relationship between video quality and bitrate for various HEVC parameters and video motion at each layer/resolution. The system architecture includes encoder/decoder configurations and how to embedded the adaptive video streaming. The encoder includes compression besi
... Show MoreThere are many studies dealt with handoff management in mobile communication systems and some of these studies presented handoff schemes to manage this important process in cellular network. All previous schemes used relative signal strength (RSS) measurements. In this work, a new proposed handoff scheme had been presented depending not only on the RSS measurements but also used the threshold distance and neighboring BSS power margins in order to improve the handoff management process. We submitted here a threshold RSS as a condition to make a handoff when a mobile station moves from one cell to another this at first, then we submitted also a specified margin between the current received signal and the ongoing BS's received signal must be s
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