Academic literature on the topic 'Adaptive bitrate streaming'
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Journal articles on the topic "Adaptive bitrate streaming"
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Kristiadi, David, and Marwiyati. "Adaptive Streaming Server dengan FFMPEG dan Golang." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (2021): 413–20. http://dx.doi.org/10.29207/resti.v5i3.2998.
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Quality of experience (QoE) when accessing video streaming becomes a challenge in varieties of network bandwidth/speed. Adaptive streaming becomes an answer to gain good QoE. An architecture system of the adaptive streaming server with Dynamic Adaptive Streaming over HTTP (DASH) was proposed. The system was consists of two services e.g transcoding and streaming. Transcoding service encodes an audio file, multi-bitrates video files, and manifest.mpd files. Streaming service serves client streaming requests that appropriate to client network profiles. The system is built using the Golang programming environment and FFMPEG. Transcoding service has some execution mode (serial and concurrent) and passing mode (1 pass and 2 passes). The transcoding service test results show that concurrent execution is faster 11,5% than the serial execution and transcoding using 1 pass is faster 46,95% than 2 passes but the bitrate of output video lower than the determinate bitrate parameter. The streaming service has a good QoE. In the 5 scenarios, buffer level=0 happens 5 times, and its total duration is 64 seconds. Buffer level=0 happens when extreme changes happen in network speed from fast to too slow.
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Jabbar, Saba Qasim, and Dheyaa Jasim Kadhim. "A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming." Journal of Engineering 27, no. 1 (2021): 112–29. http://dx.doi.org/10.31026/10.31026/j.eng.2021.01.08.
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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.
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Jabbar, Saba Qasim, and Dheyaa Jasim Kadhim. "A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming." Journal of Engineering 27, no. 1 (2021): 112–29. http://dx.doi.org/10.31026/j.eng.2021.01.08.
Full textAbstract:
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.
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Garcia, Henrique D., Mylène C. Q. Farias, Ravi Prakash, and Marcelo M. Carvalho. "Statistical characterization of tile decoding time of HEVC-encoded 360° video." Electronic Imaging 2020, no. 9 (2020): 285–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.9.iqsp-285.
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In this paper, we present a statistical characterization of tile decoding time of 360° videos encoded via HEVC that considers different tiling patterns and quality levels (i.e., bitrates). In particular, we present results for probability density function estimation of tile decoding time based on a series of experiments carried out over a set of 360° videos with different spatial and temporal characteristics. Additionally, we investigate the extent to which tile decoding time is correlated with tile bitrate (at chunk level), so that DASH-based video streaming can make possible use of such an information to infer tile decoding time. The results of this work may help in the design of queueing or control theory-based adaptive bitrate (ABR) algorithms for 360° video streaming.
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Gao, Guanyu, Yonggang Wen, and Jianfei Cai. "vCache: Supporting Cost-Efficient Adaptive Bitrate Streaming." IEEE MultiMedia 24, no. 3 (2017): 19–27. http://dx.doi.org/10.1109/mmul.2017.3051521.
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Brown, Harrison, Kai Fricke, and Eiko Yoneki. "World-Models for Bitrate Streaming." Applied Sciences 10, no. 19 (2020): 6685. http://dx.doi.org/10.3390/app10196685.
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Adaptive bitrate (ABR) algorithms optimize the quality of streaming experiences for users in client-side video players, especially in unreliable or slow mobile networks. Several rule-based heuristic algorithms can achieve stable performance, but they sometimes fail to properly adapt to changing network conditions. Fluctuating bandwidth may cause algorithms to default to behavior that creates a negative experience for the user. ABR algorithms can be generated with reinforcement learning, a decision-making paradigm in which an agent learns to make optimal choices through interactions with an environment. Training reinforcement learning algorithms for bitrate streaming requires building a simulator for an agent to experience interactions quickly; training an agent in the real environment is infeasible due to the long step times in real environments. This project explores using supervised learning to construct a world-model, or a learned simulator, from recorded interactions. A reinforcement learning agent that is trained inside of the learned model, rather than a simulator, can outperform rule-based heuristics. Furthermore, agents that are trained inside the learned world-model can outperform model-free agents in low sample regimes. This work highlights the potential for world-models to quickly learn simulators, and to be used for generating optimal policies.
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Du, Lina, Li Zhuo, Jiafeng Li, Jing Zhang, Xiaoguang Li, and Hui Zhang. "Video Quality of Experience Metric for Dynamic Adaptive Streaming Services Using DASH Standard and Deep Spatial-Temporal Representation of Video." Applied Sciences 10, no. 5 (2020): 1793. http://dx.doi.org/10.3390/app10051793.
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DASH (Dynamic Adaptive Streaming over HTTP (HyperText Transfer Protocol)) as a universal unified multimedia streaming standard selects the appropriate video bitrate to improve the user’s Quality of Experience (QoE) according to network conditions, client status, etc. Considering that the quantitative expression of the user’s QoE is also a difficult point in itself, this paper researched the distortion caused due to video compression, network transmission and other aspects, and then proposes a video QoE metric for dynamic adaptive streaming services. Three-Dimensional Convolutional Neural Networks (3D CNN) and Long Short-Term Memory (LSTM) are used together to extract the deep spatial-temporal features to represent the content characteristics of the video. While accounting for the fluctuation in the quality of a video caused by bitrate switching on the QoE, other factors such as video content characteristics, video quality and video fluency, are combined to form the input feature vector. The ridge regression method is adopted to establish a QoE metric that enables to dynamically describe the relationship between the input feature vector and the value of the Mean Opinion Score (MOS). The experimental results on different datasets demonstrate that the prediction accuracy of the proposed method can achieve superior performance over the state-of-the-art methods, which proves the proposed QoE model can effectively guide the client’s bitrate selection in dynamic adaptive streaming media services.
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Yamagishi, Kazuhisa, and Takanori Hayashi. "Parametric Quality-Estimation Model for Adaptive-Bitrate-Streaming Services." IEEE Transactions on Multimedia 19, no. 7 (2017): 1545–57. http://dx.doi.org/10.1109/tmm.2017.2669859.
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Xiao, Xuedou, Wei Wang, Taobin Chen, Yang Cao, Tao Jiang, and Qian Zhang. "Sensor-Augmented Neural Adaptive Bitrate Video Streaming on UAVs." IEEE Transactions on Multimedia 22, no. 6 (2020): 1567–76. http://dx.doi.org/10.1109/tmm.2019.2945167.
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Nguyen, Thoa, Thang Vu, Nam Pham Ngoc, and Truong Cong Thang. "SDP-Based Quality Adaptation and Performance Prediction in Adaptive Streaming of VBR Videos." Advances in Multimedia 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7323681.
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Recently, various adaptation methods have been proposed to cope with throughput fluctuations in HTTP adaptive streaming (HAS). However, these methods have mostly focused on constant bitrate (CBR) videos. Moreover, most of them are qualitative in the sense that performance metrics could only be obtained after a streaming session. In this paper, we propose a new adaptation method for streaming variable bitrate (VBR) videos using stochastic dynamic programming (SDP). With this approach, the system should have a probabilistic characterization along with the definition of a cost function that is minimized by a control strategy. Our solution is based on a new statistical model where the future streaming performance is directly related to the past bandwidth statistics. We develop mathematical models to predict and develop simulation models to measure the average performance of the adaptation policy. The experimental results show that the prediction models can provide accurate performance prediction which is useful in planning adaptation policy and that our proposed adaptation method outperforms the existing ones in terms of average quality and average quality switch.
Dissertations / Theses on the topic "Adaptive bitrate streaming"
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Dzabic, Daniel, and Mårtensson Jacob. "HTTP Based Adaptive Bitrate Streaming Protocols in Live Surveillance Systems." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152793.
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This thesis explores possible solutions to replace Adobe Flash Player by using toolsalready built into modern web browsers, and explores the tradeoffs between bitrate, qual-ity, and delay when using an adaptive bitrate for live streamed video. Using an adaptivebitrate for streamed video was found to reduce stalls in playback for the client by adapt-ing to the available bandwidth. A newer codec can further compress the video file sizewhile maintaining the same video quality. This can improve the viewing experience forclients on a restricted or a congested network. The tests conducted in this thesis showthat producing an adaptive bitrate stream and changing codecs is a very CPU intensiveprocess.
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Dzabic, Daniel, and Jacob Mårtensson. "HTTP Based Adaptive Bitrate Streaming Protocols in Live Surveillance Systems." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153097.
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This thesis explores possible solutions to replace Adobe Flash Player by using tools already built into modern web browsers, and explores the tradeoffs between bitrate, quality, and delay when using an adaptive bitrate for live streamed video. Using an adaptive bitrate for streamed video was found to reduce stalls in playback for the client by adapting to the available bandwidth. A newer codec can further compress the video file size while maintaining the same video quality. This can improve the viewing experience for clients on a restricted or a congested network. The tests conducted in this thesis show that producing an adaptive bitrate stream and changing codecs is a very CPU intensive process.
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Swärd, Rikard. "HTTP Live Streaming : En studie av strömmande videoprotokoll." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-22254.
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Användningen av strömmande video ökar snabbt just nu. Ett populärt konceptär adaptive bitrate streaming som går ut på att en video kodas i flera olikabithastigheter. Dessa videor tas sedan och delas upp i små filer och görstillgänglig via internet. När du vill spela upp en sådan video laddar du först hemen fil som beskriver vart filerna finns och i vilka bithastigheter de är kodade i.Mediaspelaren kan där efter börja ladda hem filerna och spela upp dom. Om defysiska förutsättningarna, som exempelvis nedladdningshastighet eller CPUbelastning,ändras under uppspelningen kan mediaspelaren enkelt byta kvalitépå videon genom att börja ladda filer av en annan bithastighet och slippa attvideon laggar. Denna rapport tar därför en närmare titt på fyra tekniker inomadaptive bitrate streaming. De som undersöks är HTTP Live Streaming,Dynamic Adaptive Streaming over HTTP, HTTP Dynamic Streaming ochSmooth Streaming med avseende på vilka protokoll som dom använder.Rapporten undersöker även hur Apple och FFmpeg har implementerat HTTPLive streaming med avseende på hur mycket data som behövs läsas i en filinnan videon kan börja spelas upp. Rapporten visar att det inte är så storaskillnader mellan de fyra teknikerna. Dock sticker Dynamic AdaptiveStreaming over HTTP ut lite genom att vara helt oberoende av vilket ljud ellervideoprotokoll som används. Rapporten visar också på en brist i specificeringenav HTTP Live Streaming då det inte är specificerat att första komplettabildrutan i videoströmmen bör ligga i början av filen. I Apples implementationbehövs upp till 30 kB data läsas innan uppspelning kan påbörjas medan iFFmpegs implementation är det ca 600 byte.The use of streaming video is growing rapidly at the moment. A popular conceptis adaptive bitrate streaming, which is when a video gets encoded in severaldifferent bit rates. These videos are then split into small files and made availablevia the internet. When you want to play such a video, you first download afile that describes where the files are located and in what bitrates they are encodedin. The media player then begin downloading the files and play them. Ifthe physical conditions, such as the download speed or CPU load, changes duringplayback, the media player can easily change the quality of the video bystarting to downloading files of a different bit rate and avoid that the video lags.This report will take a closer look at four techniques in adaptive bitrate streaming.They examined techniques are HTTP Live Streaming, Dynamic AdaptiveStreaming over HTTP, HTTP Dynamic Streaming and Smooth Streaming andwhich protocols they use. The report also examines how Apple and FFmpeg hasimplemented HTTP Live Streaming with respect to how much data is needed toread a file before the video can begin to be played. The report shows that thereare no large differences between the four techniques. However, Dynamic AdaptiveStreaming over HTTP stood out a bit by being completely independent ofany audio or video protocols. The report also shows a shortcoming in the specificationof HTTP Live Streaming as it is not specified that the first completeframe of the video stream should be at the beginning of the file. In Apple's implementationits needed to read up to 30 KB of data before playback can bestarted while in FFmpeg's implementation its about 600 bytes.
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Belda, Ortega Román. "Mejora del streaming de vídeo en DASH con codificación de bitrate variable mediante el algoritmo Look Ahead y mecanismos de coordinación para la reproducción, y propuesta de nuevas métricas para la evaluación de la QoE." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/169467.
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[ES] Esta tesis presenta diversas propuestas encaminadas a mejorar la transmisión de vídeo a través del estándar DASH (Dynamic Adaptive Streaming over HTTP).
Este trabajo de investigación estudia el protocolo de transmisión DASH y sus características. A la vez, plantea la codificación con calidad constante y bitrate variable como modo de codificación del contenido de vídeo más indicado para la transmisión de contenido bajo demanda mediante el estándar DASH.
Derivado de la propuesta de utilización del modo de codificación de calidad constante, cobra mayor importancia el papel que juegan los algoritmos de adaptación en la experiencia de los usuarios al consumir el contenido multimedia. En este sentido, esta tesis presenta un algoritmo de adaptación denominado Look Ahead el cual, sin modificar el estándar, permite utilizar la información de los tamaños de los segmentos de vídeo incluida en los contenedores multimedia para evitar tomar decisiones de adaptación que desemboquen en paradas no deseadas en la reproducción de contenido multimedia.
Con el objetivo de evaluar las posibles mejoras del algoritmo de adaptación presentado, se proponen tres modelos de evaluación objetiva de la QoE. Los modelos propuestos permiten predecir de forma sencilla la QoE que tendrían los usuarios de forma objetiva, utilizando parámetros conocidos como el bitrate medio, el PSNR (Peak Signal-to-Noise Ratio) y el valor de VMAF (Video Multimethod Assessment Fusion). Todos ellos aplicados a cada segmento.
Finalmente, se estudia el comportamiento de DASH en entornos Wi-Fi con alta densidad de usuarios. En este contexto, se producen un número elevado de paradas en la reproducción por una mala estimación de la tasa de transferencia disponible debida al patrón ON/OFF de descarga de DASH y a la variabilidad del acceso al medio de Wi-Fi. Para paliar esta situación, se propone un servicio de coordinación basado en la tecnología SAND (MPEG's Server and Network Assisted DASH) que proporciona una estimación de la tasa de transferencia basada en la información del estado de los players de los clientes.[CA] Aquesta tesi presenta diverses propostes encaminades a millorar la transmissió de vídeo a través de l'estàndard DASH (Dynamic Adaptive Streaming over HTTP). Aquest treball de recerca estudia el protocol de transmissió DASH i les seves característiques. Alhora, planteja la codificació amb qualitat constant i bitrate variable com a manera de codificació del contingut de vídeo més indicada per a la transmissió de contingut sota demanda mitjançant l'estàndard DASH. Derivat de la proposta d'utilització de la manera de codificació de qualitat constant, cobra major importància el paper que juguen els algorismes d'adaptació en l'experiència dels usuaris en consumir el contingut. En aquest sentit, aquesta tesi presenta un algoritme d'adaptació denominat Look Ahead el qual, sense modificar l'estàndard, permet utilitzar la informació de les grandàries dels segments de vídeo inclosa en els contenidors multimèdia per a evitar prendre decisions d'adaptació que desemboquin en una parada indesitjada en la reproducció de contingut multimèdia. Amb l'objectiu d'avaluar les possibles millores de l'algoritme d'adaptació presentat, es proposen tres models d'avaluació objectiva de la QoE. Els models proposats permeten predir de manera senzilla la QoE que tindrien els usuaris de manera objectiva, utilitzant paràmetres coneguts com el bitrate mitjà, el PSNR (Peak Signal-to-Noise Ratio) i el valor de VMAF (Video Multimethod Assessment Fusion). Tots ells aplicats a cada segment. Finalment, s'estudia el comportament de DASH en entorns Wi-Fi amb alta densitat d'usuaris. En aquest context es produeixen un nombre elevat de parades en la reproducció per una mala estimació de la taxa de transferència disponible deguda al patró ON/OFF de descàrrega de DASH i a la variabilitat de l'accés al mitjà de Wi-Fi. Per a pal·liar aquesta situació, es proposa un servei de coordinació basat en la tecnologia SAND (MPEG's Server and Network Assisted DASH) que proporciona una estimació de la taxa de transferència basada en la informació de l'estat dels players dels clients.
[EN] This thesis presents several proposals aimed at improving video transmission through the DASH (Dynamic Adaptive Streaming over HTTP) standard. This research work studies the DASH transmission protocol and its characteristics. At the same time, this work proposes the use of encoding with constant quality and variable bitrate as the most suitable video content encoding mode for on-demand content transmission through the DASH standard. Based on the proposal to use the constant quality encoding mode, the role played by adaptation algorithms in the user experience when consuming multimedia content becomes more important. In this sense, this thesis presents an adaptation algorithm called Look Ahead which, without modifying the standard, allows the use of the information on the sizes of the video segments included in the multimedia containers to avoid making adaptation decisions that lead to undesirable stalls during the playback of multimedia content. In order to evaluate the improvements of the presented adaptation algorithm, three models of objective QoE evaluation are proposed. These models allow to predict in a simple way the QoE that users would have in an objective way, using well-known parameters such as the average bitrate, the PSNR (Peak Signal-to-Noise Ratio) and the VMAF (Video Multimethod Assessment Fusion). All of them applied to each segment. Finally, the DASH behavior in Wi-Fi environments with high user density is analyzed. In this context, there could be a high number of stalls in the playback because of a bad estimation of the available transfer rate due to the ON/OFF pattern of DASH download and to the variability of the access to the Wi-Fi environment. To relieve this situation, a coordination service based on SAND (MPEG's Server and Network Assisted DASH) is proposed, which provides an estimation of the transfer rate based on the information of the state of the clients' players.
Belda Ortega, R. (2021). Mejora del streaming de vídeo en DASH con codificación de bitrate variable mediante el algoritmo Look Ahead y mecanismos de coordinación para la reproducción, y propuesta de nuevas métricas para la evaluación de la QoE [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/169467
TESIS
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Mazza, Stefano. "Implementazione e analisi di algoritmi dinamici per trasmissione MPEG-DASH su client Android." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11875/.
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Attualmente, la maggior parte dei dati che transitano sulla rete appartiene a contenuti multimediali. Più nello specifico, è lo Streaming Video ad avere la predominanza nella condivisione di Internet; vista la crescita che tale servizio ha subìto negli ultimi anni, si sono susseguiti diversi studi volti allo sviluppo di tecniche e metodologie che potessero migliorarlo. Una di queste è sicuramente l'Adaptive Video Streaming, tecnica utilizzata per garantire all'utente una buona Quality of Experience (QoE) mediante l'utilizzo dei cosiddetti "algoritmi di rate adaptation".
Il lavoro svolto in questi studi si è voluto concentrare su due filoni distinti, ma allo stesso tempo confrontabili: la prima parte della tesi riguarda lo sviluppo e l'analisi di alcuni algoritmi di rate adaptation per DASH, mentre la seconda è relativa all'implementazione di un nuovo algoritmo che li possa affiancare, migliorando la QoE nel monitorare lo stato della connessione.
Si è quindi dovuta implementare un'applicazione Android per lo streaming video, che fosse conforme allo standard MPEG-DASH e potesse fornire le informazioni di testing da utilizzare per le analisi.
La tesi è suddivisa in quattro capitoli: il primo introduce l'argomento e definisce la terminologia necessaria alla comprensione degli studi; il secondo descrive alcuni dei lavori correlati allo streaming adattivo e introduce i due filoni principali della tesi, ovvero gli algoritmi di rate adaptation e la proposta di algoritmo per la selezione dinamica del segmento; il terzo presenta l'app SSDash, utilizzata come mezzo per le analisi sperimentali; infine, il quarto ed ultimo capitolo mostra i risultati delle analisi e le corrispondenti valutazioni.
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Lin, Kuei-Hong, and 林奎宏. "Adaptive Bitrate Streaming over Software Defined Networks." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/r8us6y.
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碩士國立交通大學
電機學院電信學程
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Video streaming is one of the most popular real-time Internet services which has changed the viewing behaviors of millions of people around the world. A novel streaming technique called adaptive bitrate streaming (ABS) that allocates appropriate video bitrates based on the current overall network capacity (especially CPU and memory) and traffic condition can minimize the buffering requirement and provide satisfactory user experiences to all viewers. By monitoring the network condition and evaluating the available bandwidth continuously, an ABS client adaptively selects an appropriate video bitrate. However, conventional ABS techniques endow each individual client with full authority to determine the desired bandwidth. Each client thus unilaterally observes the network traffic and makes a video bitrate decision which serves its demand best. The distributed decisions entail unfairness in bandwidth allocation as ABS clients tend to overestimate the required bandwidth. As a result, some may be allocated more bandwidth than actually needed while others receive less than they really need. Furthermore, an overestimation may cause an underestimation in the next iteration, ultimately bringing the clients with unstable video bitrates and poor quality of experience (QoE). To evaluate QoE in video streaming services, video quality is often used as a proper metric. Thus, optimizing QoE is equivalent to optimizing the “video quality” fairness. We formulate the QoE optimization problem as a maximum minimum fairness (MMF) problem. It essentially searches for a candidate bandwidth allocation (in bitrate) and the corresponded video quality for all the clients so that the worst client video quality fairness is maximized. Three schemes are proposed to solve the MMF problem. On the other hand, for these solutions to be implementable, the information regarding the network conditions of all clients should be available to a resource allocation agent. It is clear this is realizable only if the network in question has a software defined architecture. A software defined network (SDN) has a centralized controller platform which continuously monitors the overall network condition and collects related information to manage flow control for intelligent networking. The ABS clients need not to make bitrate decisions but simply forward the observed network traffic and storage status to the SDN controller. Based on the SDN architecture, our numerical solution gives a resource allocation policy for ABS clients to achieve the mini-max QoE fairness in real-time. Both computer simulation and hardware implementation results are provided to verify the feasibility and efficiency of the proposed methods. We find that all three algorithms achieve the same QoE fairness (i.e., MMF).
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Deshmukh, Rajvardhan Somraj. "Improving Resilience of Communication in Information Dissemination for Time-Critical Applications." 2019. https://scholarworks.umass.edu/masters_theses_2/768.
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Severe weather impacts life and in this dire condition, people rely on communication, to organize relief and stay in touch with their loved ones. In such situations, cellular network infrastructure\footnote{We refer to cellular network infrastructure as infrastructure for the entirety of this document} might be affected due to power outage, link failures, etc. This urges us to look at Ad-hoc mode of communication, to offload major traffic partially or fully from the infrastructure, depending on the status of it.
We look into threefold approach, ranging from the case where the infrastructure is completely unavailable, to where it has been replaced by make shift low capacity mobile cellular base station.
First, we look into communication without infrastructure and timely, dissemination of weather alerts specific to geographical areas. We look into the specific case of floods as they affect significant number of people. Due to the nature of the problem we can utilize the properties of Information Centric Networking (ICN) in this context, namely: i) Flexibility and high failure resistance: Any node in the network that has the information can satisfy the query ii) Robust: Only sensor and car need to communicate iii) Fine grained geo-location specific information dissemination. We analyze how message forwarding using ICN on top of Ad hoc network, approach compares to the one based on infrastructure, that is less resilient in the case of disaster. In addition, we compare the performance of different message forwarding strategies in VANETs (Vehicular Adhoc Networks) using ICN. Our results show that ICN strategy outperforms the infrastructure-based approach as it is 100 times faster for 63\% of total messages delivered.
Then we look into the case where we have the cellular network infrastructure, but it is being pressured due to rapid increase in volume of network traffic (as seen during a major event) or it has been replaced by low capacity mobile tower. In this case we look at offloading as much traffic as possible from the infrastructure to device-to-device communication. However, the host-oriented model of the TCP/IP-based Internet poses challenges to this communication pattern. A scheme that uses an ICN model to fetch content from nearby peers, increases the resiliency of the network in cases of outages and disasters. We collected content popularity statistics from social media to create a content request pattern and evaluate our approach through the simulation of realistic urban scenarios. Additionally, we analyze the scenario of large crowds in sports venues. Our simulation results show that we can offload traffic from the backhaul network by up to 51.7\%, suggesting an advantageous path to support the surge in traffic while keeping complexity and cost for the network operator at manageable levels.
Finally, we look at adaptive bit-rate streaming (ABR) streaming, which has contributed significantly to the reduction of video playout stalling, mainly in highly variable bandwidth conditions. ABR clients continue to suffer from the variation of bit rate qualities over the duration of a streaming session. Similar to stalling, these variations in bit rate quality have a negative impact on the users’ Quality of Experience (QoE). We use a trace from a large-scale CDN to show that such quality changes occur in a significant amount of streaming sessions and investigate an ABR video segment retransmission approach to reduce the number of such quality changes. As the new HTTP/2 standard is becoming increasingly popular, we also see an increase in the usage of HTTP/2 as an alternative protocol for the transmission of web traffic including video streaming. Using various network conditions, we conduct a systematic comparison of existing transport layer approaches for HTTP/2 that is best suited for ABR segment retransmissions. Since it is well known that both protocols provide a series of improvements over HTTP/1.1, we perform experiments both in controlled environments and over transcontinental links in the Internet and find that these benefits also “trickle up” into the application layer when it comes to ABR video streaming where HTTP/2 retransmissions can significantly improve the average quality bitrate while simultaneously minimizing bit rate variations over the duration of a streaming session. Taking inspiration from the first two approaches, we take into account the resiliency of a multi-path approach and further look at a multi-path and multi-stream approach to ABR streaming and demonstrate that losses on one path have very little impact on the other from the same multi-path connection and this increases throughput and resiliency of communication.
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Suresh, Bhushan. "AN EVALUATION OF SDN AND NFV SUPPORT FOR PARALLEL, ALTERNATIVE PROTOCOL STACK OPERATIONS IN FUTURE INTERNETS." 2018. https://scholarworks.umass.edu/masters_theses_2/667.
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Virtualization on top of high-performance servers has enabled the virtualization of network functions like caching, deep packet inspection, etc. Such Network Function Virtualization (NFV) is used to dynamically adapt to changes in network traffic and application popularity. We demonstrate how the combination of Software Defined Networking (SDN) and NFV can support the parallel operation of different Internet architectures on top of the same physical hardware. We introduce our architecture for this approach in an actual test setup, using CloudLab resources. We start of our evaluation in a small setup where we evaluate the feasibility of the SDN and NFV architecture and incrementally increase the complexity of the setup to run a live video streaming application. We use two vastly different protocol stacks, namely TCP/IP and NDN to demonstrate the capability of our approach. The evaluation of our approach shows that it introduces a new level of flexibility when it comes to operation of different Internet architectures on top of the same physical network and with this flexibility provides the ability to switch between the two protocol stacks depending on the application.
Book chapters on the topic "Adaptive bitrate streaming"
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Sharif, Usman, Adnan N. Qureshi, and Seemal Afza. "ORTIA: An Algorithm to Improve Quality of Experience in HTTP Adaptive Bitrate Streaming Sessions." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55190-2_3.
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Fleury, Martin, and Laith Al-Jobouri. "Techniques and Tools for Adaptive Video Streaming." In Intelligent Multimedia Technologies for Networking Applications. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2833-5.ch004.
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Adaptive video streaming is becoming increasingly necessary as quality expectations rise, while congestion persists and the extension of the Internet to mobile access creates new sources of packet loss. This chapter considers several techniques for adaptive video streaming including live HTTP streaming, bitrate transcoding, scalable video coding, and rate controllers. It also includes additional case studies of congestion control over the wired Internet using fuzzy logic, statistical multiplexing to adapt constant bitrate streams to the bandwidth capacity, and adaptive error correction for the mobile Internet. To guide the reader, the chapter makes a number of comparisons between the main techniques, for example explaining why currently per-encoded video may be better-streamed using adaptive simulcast than by transcoding or scalable video coding.
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Rovcanin, Lejla, and Gabriel-Miro Muntean. "DASH." In Convergence of Broadband, Broadcast, and Cellular Network Technologies. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5978-0.ch007.
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Multimedia streaming has major commercial potential as the global community of online video viewers is expanding rapidly following the proliferation of low-cost multimedia-enabled mobile devices. These devices enable increasing amounts of video-based content to be acquired, stored, and distributed across existing best effort networks that also carry other traffic types. Although a number of protocols are used for video transfer, a significant portion of the Internet streaming media is currently delivered over Hypertext Transfer Protocol (HTTP). Network congestion is one of the most important issues that affects networking traffic in general and video content delivery. Among the various solutions proposed, adaptive delivery of content according to available network bandwidth was very successful. In this context, the most recent standardisation efforts have focused on the introduction of the Dynamic Adaptive Streaming over HTTP (DASH) (ISO, 2012) standard. DASH offers support for client-based bitrate video streaming adaptation, but as it does not introduce any particular adaptation mechanism, it relies on third party solutions to complement it. This chapter provides an overview of the DASH standard and presents a short survey of currently proposed mechanisms for video adaptation related to DASH. It also introduces the DASH-aware Performance-Oriented Adaptation Agent (dPOAA), which improves user Quality of Experience (QoE) levels by dynamically selecting best performing sources for the delivery of video content. dPOAA, in its functionality, considers the characteristics of the network links connecting clients with video providers. dPOAA can be utilised as a DASH player plugin or in conjunction with the DASH-based performance-oriented Adaptive Video Distribution solution (DAV) (Rovcanin & Muntean, 2013), which considers the local network characteristics, quantity of requested content available locally, and device and user profiles.
Conference papers on the topic "Adaptive bitrate streaming"
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Reznik, Yuriy A., Xiangbo Li, Karl O. Lillevold, Abhijith Jagannath, and Justin Greer. "Optimal Multi-Codec Adaptive Bitrate Streaming." In 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2019. http://dx.doi.org/10.1109/icmew.2019.00066.
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Kimura, Takuto, Tatsuaki Kimura, and Kazuhisa Yamagishi. "Context-aware Adaptive Bitrate Streaming System." In ICC 2021 - IEEE International Conference on Communications. IEEE, 2021. http://dx.doi.org/10.1109/icc42927.2021.9500665.
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Lebreton, Pierre, and Kazuhisa Yamagishi. "Network and Content-Dependent Bitrate Ladder Estimation for Adaptive Bitrate Video Streaming." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413558.
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Le, Hung T., Duc V. Nguyen, Nam Pham Ngoc, Anh T. Pham, and Truong Cong Thang. "Buffer-based bitrate adaptation for adaptive HTTP streaming." In 2013 International Conference on Advanced Technologies for Communications (ATC 2013). IEEE, 2013. http://dx.doi.org/10.1109/atc.2013.6698072.
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Nandakumar, D., P. Ramachandran, S. Kotecha, T. Vaughan, and K. Sampath. "Efficient multi-bitrate HEVC encoding for adaptive streaming." In IBC 2016 Conference. Institution of Engineering and Technology, 2016. http://dx.doi.org/10.1049/ibc.2016.0036.
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Huang, Tianchi, Rui-Xiao Zhang, and Lifeng Sun. "Deep reinforced bitrate ladders for adaptive video streaming." In MMSys '21: 12th ACM Multimedia Systems Conference. ACM, 2021. http://dx.doi.org/10.1145/3458306.3458873.
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Katsenou, Angeliki V., Fan Zhang, Kyle Swanson, Mariana Afonso, Joel Sole, and David R. Bull. "VMAF-based Bitrate Ladder Estimation for Adaptive Streaming." In 2021 Picture Coding Symposium (PCS). IEEE, 2021. http://dx.doi.org/10.1109/pcs50896.2021.9477469.
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Takahashi, Shoko, Kazuhisa Yamagishi, and Jun Okamoto. "Classification of Viewing Abandonment Reasons for Adaptive Bitrate Streaming." In 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 2020. http://dx.doi.org/10.1109/qomex48832.2020.9123146.
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Alt, Bastian, Trevor Ballard, Ralf Steinmetz, Heinz Koeppl, and Amr Rizk. "CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. IEEE, 2019. http://dx.doi.org/10.1109/infocom.2019.8737418.
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Nguyen, Duc V., Dung M. Nguyen, Huyen T. Tran, Nam Pham Ngoc, Anh T. Pham, and Truong C. Thang. "Quality-delay tradeoff optimization in multi-bitrate adaptive streaming." In 2015 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2015. http://dx.doi.org/10.1109/icce.2015.7066320.
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