10,672 research outputs found

    Upload Data Rate for Optimal First Chunk Download Time for P2P based Video on Demand (VoD) Services

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    Video on demand (VoD) systems are the one of the emerging content distribution mechanism as it adds lots of conveniences and choices to the users where they can watch Video as per their will asynchronously. But, the implementation of such system faces lots of challenges such as wait-time for starting of the service, download time of the whole video content to provide continuous & unhindered services etc. In this paper we have studied the relation between download time of first chunk and the whole video if the bandwidth is limited in perspective of upload rate in P2P based Video on demand system. Here, we find out at what Upload data rate, we can get best of trade-offs between first chunk download time and whole video download time in order to continuous and unhindered services. DOI: 10.17762/ijritcc2321-8169.150510

    Challenges of digital innovations : a set-top box based approach

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    The chapter analyses the challenges of digital technology for television audience measurement systems. First, the current state of audience measurement in Belgium is described. In the Belgian case, the traditional television audience measurement system is contested by small broadcasters and challenged by the opportunities that the emergence of digital television and, more specifically, the widespread diffusion of set-top boxes provide. Second, three major challenges for traditional measurement techniques are analysed. This section deals with people’s changing viewing habits, for example on-demand and time-shifted viewing, the provision of more accurate data by set-top boxes, and the increasing interests of platform operators acting as gatekeepers to access to this data. In the final section, conclusions are made

    Interactivity And User-heterogeneity In On Demand Broadcast Video

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    Video-On-Demand (VOD) has appeared as an important technology for many multimedia applications such as news on demand, digital libraries, home entertainment, and distance learning. In its simplest form, delivery of a video stream requires a dedicated channel for each video session. This scheme is very expensive and non-scalable. To preserve server bandwidth, many users can share a channel using multicast. Two types of multicast have been considered. In a non-periodic multicast setting, users make video requests to the server; and it serves them according to some scheduling policy. In a periodic broadcast environment, the server does not wait for service requests. It broadcasts a video cyclically, e.g., a new stream of the same video is started every t seconds. Although, this type of approach does not guarantee true VOD, the worst service latency experienced by any client is less than t seconds. A distinct advantage of this approach is that it can serve a very large community of users using minimal server bandwidth. In VOD System it is desirable to provide the user with the video-cassette-recorder-like (VCR) capabilities such as fast-forwarding a video or jumping to a specific frame. This issue in the broadcast framework is addressed, where each video and its interactive version are broadcast repeatedly on the network. Existing techniques rely on data prefetching as the mechanism to provide this functionality. This approach provides limited usability since the prefetching rate cannot keep up with typical fast-forward speeds. In the same environment, end users might have access to different bandwidth capabilities at different times. Current periodic broadcast schemes, do not take advantage of high-bandwidth capabilities, nor do they adapt to the low-bandwidth limitation of the receivers. A heterogeneous technique is presented that can adapt to a range of receiving bandwidth capability. Given a server bandwidth and a range of different client bandwidths, users employing the proposed technique will choose either to use their full reception bandwidth capability and therefore accessing the video at a very short time, or using part or enough reception bandwidth at the expense of a longer access latency

    Traffic analysis of Internet user behavior and content demand patterns

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    El estudio del trafico de internet es relevante para poder mejorar la calidad de servicio de los usuarios. Ser capaz de conocer cuales son los servicios más populares y las horas con más usuarios activos permite identificar la cantidad de tráfico producido y, por lo tanto, diseñar una red capaz de soportar la actividad esperada. La implementación de una red considerando este conocimiento puede reducir el tiempo de espera considerablemente, mejorando la experiencia de los usuarios en la web. Ya existen análisis del trafico de los usuarios y de sus patrones de demanda. Pero, los datos utilizados en estos estudios no han sido renovados, por lo tanto los resultados obtenidos pueden estar obsoletos y se han podido producir cambios importantes. En esta tesis, se estudia la cantidad de trafico entrante y saliente producido por diferentes aplicaciones y se ha hecho una evolución teniendo en cuenta datos presentes y pasados. Esto nos permitirá entender los cambios producidos desde 2007 hasta 2015 y observar las tendencias actuales. Además, se han analizado los patrones de demanda de usuarios del inicio de 2016 y se han comparado con resultados previos. La evolución del tráfico demuestra cambios en las preferencias de los usuarios, a pesar de que los patrones de demanda siguen siendo los mismos que en años anteriores. Los resultados obtenidos en esta tesis confirman las predicciones sobre un aumento del tráfico de 'Streaming Media'; se ha comprobado que el tráfico de 'Streaming Media' es el tráfico total dominante, con Netflix como el mayor contribuidor.L'estudi del trànsit d'Internet és rellevant per a poder millor la qualitat de servei dels usuaris. Ser capaç de conèixer quins són els serveis més popular i les hores amb més usuaris actius permet identificar la quantitat de trànsit produït i, per tant, dissenyar una xarxa capaç de soportar la activitat esperada. L'implementació d'una xarxa considerant aquest coneixement pot reduir el temps d'espera considerablement, millorant l'experiència dels usuaris a la web. Ja existeixen anàlisis del transit dels usuaris i els seus patrons de demanda. Però, les dades utilitzades en aquests estudis no han sigut renovades, per tant els resultats obtinguts poden estar obsolets i s'han produït canvis importants. En aquesta tesis, s'estudia la quantitat de transit entrant i sortint produit per diferents aplicacions i s'ha fet una evolució, tenint en compte dades presents i passades. Això ens permetrà entendre els canvis produïts des de 2007 fins 2015 i observar les tendències actuals. A més, s'han analitzat els patrons de demanda de usuaris de principis de 2016 i s'han comparat amb resultats previs. L'evolució del trànsit mostra canvis en las preferències dels usuaris, en canvi els patrons de demanda continuen sent els mateixos que en anys posteriors. Els resultats obtinguts en aquesta tesis confirmen les prediccions sobre un augment del trànsit de 'Streaming Media'; s'ha comprovat que el trànsit de 'Streaming Media' es el trànsit total dominant, amb Netflix com el major contribuïdor.The study of Internet traffic is relevant in order to improve the quality of service of users. Being able to know which are the most popular services and the hours with most active users can let us identify the amount of inbound and outbound traffic produced, and hence design a network able to support the activity expected. The implementation of a network considering that knowledge can reduce the waiting time of users considerably, improving the users’ experience in the web. Analysis of users’ traffic and user demand patterns already exist. However, the data used in these studies is not renewed, thus the results found can be obsolete and considerable changes would have happened. In this bachelor’s thesis, it is studied the amount of inbound and outbound traffic produced considering different applications and the evolution when regarding previous and actual data has been taken into account. This would let us understand the changes produced from 2007 to 2015 and observe the tendencies nowadays. In addition, it has been analyzed the user demand patterns in the beginning of 2016 and it has been contrasted with previous results. The evolution of traffic has shown changes in users’ preferences, although their demand patterns are still the same as previous years. The results found in this thesis confirmed the expectations about an increase of streaming media Internet traffic; it was proved that streaming media traffic is the dominant total traffic, with Netflix as the major contributor

    Control of Multiple Remote Servers for Quality-Fair Delivery of Multimedia Contents

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    This paper proposes a control scheme for the quality-fair delivery of several encoded video streams to mobile users sharing a common wireless resource. Video quality fairness, as well as similar delivery delays are targeted among streams. The proposed controller is implemented within some aggregator located near the bottleneck of the network. The transmission rate among streams is adapted based on the quality of the already encoded and buffered packets in the aggregator. Encoding rate targets are evaluated by the aggregator and fed back to each remote video server (fully centralized solution), or directly evaluated by each server in a distributed way (partially distributed solution). Each encoding rate target is adjusted for each stream independently based on the corresponding buffer level or buffering delay in the aggregator. Communication delays between the servers and the aggregator are taken into account. The transmission and encoding rate control problems are studied with a control-theoretic perspective. The system is described with a multi-input multi-output model. Proportional Integral (PI) controllers are used to adjust the video quality and control the aggregator buffer levels. The system equilibrium and stability properties are studied. This provides guidelines for choosing the parameters of the PI controllers. Experimental results show the convergence of the proposed control system and demonstrate the improvement in video quality fairness compared to a classical transmission rate fair streaming solution and to a utility max-min fair approach

    Cooperative announcement-based caching for video-on-demand streaming

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    Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth
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