Modeling and Evaluation of Multisource Streaming Strategies in P2P VoD Systems

In recent years, multimedia content distribution has largely been moved to the Internet, inducing broadcasters, operators and service providers to upgrade with large expenses their infrastructures. In this context, streaming solutions that rely on user devices such as set-top boxes (STBs) to offload dedicated streaming servers are particularly appropriate. In these systems, contents are usually replicated and scattered over the network established by STBs placed at users' home, and the video-on-demand (VoD) service is provisioned through streaming sessions established among neighboring STBs following a Peer-to-Peer fashion. Up to now the majority of research works have focused on the design and optimization of content replicas mechanisms to minimize server costs. The optimization of replicas mechanisms has been typically performed either considering very crude system performance indicators or analyzing asymptotic behavior. In this work, instead, we propose an analytical model that complements previous works providing fairly accurate predictions of system performance (i.e., blocking probability). Our model turns out to be a highly scalable, flexible, and extensible tool that may be helpful both for designers and developers to efficiently predict the effect of system design choices in large scale STB-VoD system

End-to-end resource management for federated delivery of multimedia services

Recently, the Internet has become a popular platform for the delivery of multimedia content. Currently, multimedia services are either offered by Over-the-top (OTT) providers or by access ISPs over a managed IP network. As OTT providers offer their content across the best-effort Internet, they cannot offer any Quality of Service (QoS) guarantees to their users. On the other hand, users of managed multimedia services are limited to the relatively small selection of content offered by their own ISP. This article presents a framework that combines the advantages of both existing approaches, by dynamically setting up federations between the stakeholders involved in the content delivery process. Specifically, the framework provides an automated mechanism to set up end-to-end federations for QoS-aware delivery of multimedia content across the Internet. QoS contracts are automatically negotiated between the content provider, its customers, and the intermediary network domains. Additionally, a federated resource reservation algorithm is presented, which allows the framework to identify the optimal set of stakeholders and resources to include within a federation. Its goal is to minimize delivery costs for the content provider, while satisfying customer QoS requirements. Moreover, the presented framework allows intermediary storage sites to be included in these federations, supporting on-the-fly deployment of content caches along the delivery paths. The algorithm was thoroughly evaluated in order to validate our approach and assess the merits of including intermediary storage sites. The results clearly show the benefits of our method, with delivery cost reductions of up to 80 % in the evaluated scenario

Data compression and transmission aspects of panoramic videos

Panoramic videos are effective means for representing static or dynamic scenes along predefined paths. They allow users to change their viewpoints interactively at points in time or space defined by the paths. High-resolution panoramic videos, while desirable, consume a significant amount of storage and bandwidth for transmission. They also make real-time decoding computationally very intensive. This paper proposes efficient data compression and transmission techniques for panoramic videos. A high-performance MPEG-2-like compression algorithm, which takes into account the random access requirements and the redundancies of panoramic videos, is proposed. The transmission aspects of panoramic videos over cable networks, local area networks (LANs), and the Internet are also discussed. In particular, an efficient advanced delivery sharing scheme (ADSS) for reducing repeated transmission and retrieval of frequently requested video segments is introduced. This protocol was verified by constructing an experimental VOD system consisting of a video server and eight Pentium 4 computers. Using the synthetic panoramic video Village at a rate of 197 kb/s and 7 f/s, nearly two-thirds of the memory access and transmission bandwidth of the video server were saved under normal network traffic.published_or_final_versio

Network overload avoidance by traffic engineering and content caching

The Internet traffic volume continues to grow at a great rate, now driven by video and TV distribution. For network operators it is important to avoid congestion in the network, and to meet service level agreements with their customers. This thesis presents work on two methods operators can use to reduce links loads in their networks: traffic engineering and content caching. This thesis studies access patterns for TV and video and the potential for caching. The investigation is done both using simulation and by analysis of logs from a large TV-on-Demand system over four months. The results show that there is a small set of programs that account for a large fraction of the requests and that a comparatively small local cache can be used to significantly reduce the peak link loads during prime time. The investigation also demonstrates how the popularity of programs changes over time and shows that the access pattern in a TV-on-Demand system very much depends on the content type. For traffic engineering the objective is to avoid congestion in the network and to make better use of available resources by adapting the routing to the current traffic situation. The main challenge for traffic engineering in IP networks is to cope with the dynamics of Internet traffic demands. This thesis proposes L-balanced routings that route the traffic on the shortest paths possible but make sure that no link is utilised to more than a given level L. L-balanced routing gives efficient routing of traffic and controlled spare capacity to handle unpredictable changes in traffic. We present an L-balanced routing algorithm and a heuristic search method for finding L-balanced weight settings for the legacy routing protocols OSPF and IS-IS. We show that the search and the resulting weight settings work well in real network scenarios

Traffic analysis of Internet user behavior and content demand patterns

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