536 research outputs found

    Better Admission Control and Disk Scheduling for Multimedia Applications

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    General purpose operating systems have been designed to provide fast, loss-free disk service to all applications. However, multimedia applications are capable of tolerating some data loss, but are very sensitive to variation in disk service timing. Present research efforts to handle multimedia applications assume pessimistic disk behaviour when deciding to admit new multimedia connections so as not to violate the real-time application constraints. However, since multimedia applications are ``soft\u27 real-time applications that can tolerate some loss, we propose an optimistic scheme for admission control which uses average case values for disk access. Typically, disk scheduling mechanisms for multimedia applications reduce disk access times by only trying to minimize movement to subsequent blocks after sequencing based on Earliest Deadline First. We propose to implement a disk scheduling algorithm that uses knowledge of the media stored and permissible loss and jitter for each client, in addition to the physical parameters used by the other scheduling algorithms. We will evaluate our approach by implementing our admission control policy and disk scheduling algorithm in Linux and measuring the quality of various multimedia streams. If successful, the contributions of this thesis are the development of new admission control and flexible disk scheduling algorithm for improved multimedia quality of service

    Building Internet caching systems for streaming media delivery

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    The proxy has been widely and successfully used to cache the static Web objects fetched by a client so that the subsequent clients requesting the same Web objects can be served directly from the proxy instead of other sources faraway, thus reducing the server\u27s load, the network traffic and the client response time. However, with the dramatic increase of streaming media objects emerging on the Internet, the existing proxy cannot efficiently deliver them due to their large sizes and client real time requirements.;In this dissertation, we design, implement, and evaluate cost-effective and high performance proxy-based Internet caching systems for streaming media delivery. Addressing the conflicting performance objectives for streaming media delivery, we first propose an efficient segment-based streaming media proxy system model. This model has guided us to design a practical streaming proxy, called Hyper-Proxy, aiming at delivering the streaming media data to clients with minimum playback jitter and a small startup latency, while achieving high caching performance. Second, we have implemented Hyper-Proxy by leveraging the existing Internet infrastructure. Hyper-Proxy enables the streaming service on the common Web servers. The evaluation of Hyper-Proxy on the global Internet environment and the local network environment shows it can provide satisfying streaming performance to clients while maintaining a good cache performance. Finally, to further improve the streaming delivery efficiency, we propose a group of the Shared Running Buffers (SRB) based proxy caching techniques to effectively utilize proxy\u27s memory. SRB algorithms can significantly reduce the media server/proxy\u27s load and network traffic and relieve the bottlenecks of the disk bandwidth and the network bandwidth.;The contributions of this dissertation are threefold: (1) we have studied several critical performance trade-offs and provided insights into Internet media content caching and delivery. Our understanding further leads us to establish an effective streaming system optimization model; (2) we have designed and evaluated several efficient algorithms to support Internet streaming content delivery, including segment caching, segment prefetching, and memory locality exploitation for streaming; (3) having addressed several system challenges, we have successfully implemented a real streaming proxy system and deployed it in a large industrial enterprise

    System analysis of a Peer-to-Peer Video-on-Demand architecture : Kangaroo

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    Architectural design and deployment of Peer-to-Peer Video-on-Demand (P2PVoD) systems which support VCR functionalities is attracting the interest of an increasing number of research groups within the scientific community; especially due to the intrinsic characteristics of such systems and the benefits that peers could provide at reducing the server load. This work focuses on the performance analysis of a P2P-VoD system considering user behaviors obtained from real traces together with other synthetic user patterns. The experiments performed show that it is feasible to achieve a performance close to the best possible. Future work will consider monitoring the physical characteristics of the network in order to improve the design of different aspects of a VoD system.El disseny arquitectònic i el desplegament de sistemes de Vídeo sota Demanda "Peer-to-Peer" que soporten funcionalitats VCR està captant l'interès d'un nombre creixent de grups de recerca a la comunitat científica, degut especialment a les característiques intrínsiques dels mencionats sistemes i als beneficis que els peers podrien proporcionar a la reducció de la càrrega en el servidor. Aquest treball tracta l'anàlisi del rendiment d'un sistema P2P-VoD considerant el comportament d'usuaris obtingut amb traçes reals i amb patrons sintètics. Els experiments realitzats mostren que és viable assolir un rendiment proper al cas més óptim. Com treball futur es considerarà la monitorització de les característiques físiques de la xarxa per a poder millorar el disseny dels diferents aspectes que formen un sistema de VoD.El diseño arquitectónico y el despliegue de sistemas de Video bajo Demanda "Peer-to-Peer" que soportan funcionalidades VCR está captando el interés de un número creciente de grupos de investigación dentro de la comunidad científica; especialmente debido a las características intrínsecas de tales sistemas y a los beneficios que los peers podrían proporcionar en la reducción de la carga en el servidor. Este trabajo se enfoca en el análisis de rendimiento de un sistema P2PVoD considerando el comportamiento de usuarios obtenido de trazas reales, junto a otros patrones sintéticos. Los experimentos realizados muestran que es viable lograr un rendimiento cercano al caso más óptimo. El trabajo futuro considerará la monitorización de las características físicas de la red para poder mejorar el diseño de los diferentes aspectos que conforman un sistema de VoD

    Adaptive Prefetching for Device-Independent File I/O

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    Device independent I/O has been a holy grail to operating system designers since the early days of UNIX. Unfortunately, existing operating systems fall short of this goal for multimedia applications. Techniques such as caching and sequential read-ahead can help mask I/O latency in some cases, but in others they increase latency and add substantial jitter. Multimedia applications, such as video players, are sensitive to vagaries in performance since I/O latency and jitter affect the quality of presentation. Our solution uses adaptive prefetching to reduce both latency and jitter. Applications submit file access plans to the prefetcher, which then generates I/O requests to the operating system and manages the buffer cache to isolate the application from variations in device performance. Our experiments show device independence can be achieved: an MPEG video player sees the same latency when reading from a local disk or an NFS server. Moreover, our approach reduces jitter substantially

    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
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