Interactivity And User-heterogeneity In On Demand Broadcast Video

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

Design and performance analysis of a super-scalar video-on-demand system.

Lee Chung Hing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 61-63).Abstracts in English and Chinese.Acknowledgements --- p.iiAbstract --- p.iiiList of Figures --- p.viiChapter 1. --- Introduction --- p.1Chapter 1.1 --- Contributions of This Thesis --- p.3Chapter 1.2 --- Organizations of This Thesis --- p.3Chapter 1.3 --- Publication --- p.4Chapter 2. --- Overview of VoD Systems --- p.5Chapter 2.1 --- True VoD --- p.6Chapter 2.2 --- Near VoD --- p.7Chapter 2.3 --- Related Works --- p.9Chapter 2.3.1 --- Batching --- p.9Chapter 2.3.2 --- Patching --- p.11Chapter 2.3.3 --- Mcache --- p.11Chapter 2.3.4 --- Unified VoD --- p.12Chapter 2.4 --- Discussions --- p.15Chapter 3. --- Super-Scalar Architecture --- p.17Chapter 3.1 --- Transmission Scheduling --- p.20Chapter 3.2 --- Admission Control --- p.21Chapter 3.3 --- Channel Merging --- p.26Chapter 3.4 --- Interactive Control --- p.29Chapter 4. --- Performance Modeling --- p.31Chapter 4.1 --- Waiting Time for Statically-Admitted Clients --- p.32Chapter 4.2 --- Waiting Time for Dynamically-Admitted Clients --- p.33Chapter 4.3 --- Admission Threshold --- p.38Chapter 4.4 --- Channel Partitioning --- p.39Chapter 5. --- Performance Evaluation --- p.40Chapter 5.1 --- Model Validation --- p.40Chapter 5.2 --- Channel Partitioning --- p.42Chapter 5.3 --- Latency Comparisons --- p.44Chapter 5.4 --- Channel Requirement --- p.46Chapter 5.5 --- Performance at Light Loads --- p.47Chapter 5.6 --- Multiplexing Gain --- p.49Chapter 6. --- Implementation and Benchmarking --- p.51Chapter 6.1 --- Implementation Description --- p.51Chapter 6.2 --- Benchmarking --- p.53Chapter 6.2.1 --- Benchmarking Setup --- p.53Chapter 6.2.2 --- Benchmarking Result --- p.55Chapter 7. --- Conclusion --- p.56Appendix --- p.57Bibliography --- p.6

Ad-hoc Stream Adaptive Protocol

With the growing market of smart-phones, sophisticated applications that do extensive computation are common on mobile platform; and with consumers’ high expectation of technologies to stay connected on the go, academic researchers and industries have been making efforts to find ways to stream multimedia contents to mobile devices. However, the restricted wireless channel bandwidth, unstable nature of wireless channels, and unpredictable nature of mobility, has been the major road block for wireless streaming advance forward. In this paper, various recent studies on mobility and P2P system proposal are explained and analyzed, and propose a new design based on existing P2P systems, aimed to solve the wireless and mobility issues

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

Quality of Service based Retrieval Strategy for Distributed Video on Demand on Multiple Servers

The recent advances and development of inexpensive computers and high speed networking technology have enabled the Video on Demand (VoD) application to connect to shared-computing servers, replacing the traditional computing environments where each application was having its own dedicated computing hardware. The VoD application enables the viewer to select, from a list of video files, his favorite video file and watch its reproduction at will. Early video on demand applications were based on single video server where video streams are initiated from a single server, then with the increase in the number of the clients who became interested in VoD services, the focus became on Distributed VoD architectures (DVoD) where the context of distribution may be distributed system components, distributed streaming servers, distributed media content etc.The VoD server must handle several issues in order to be able to present a successful service. It has to receive the clients’ requests and analyze them, calculate the necessary resources for each request, and decide whether a request can be admitted or not. Once the request is admitted, the server must schedule the request, retrieve the required video data and send the video data in a timely manner so that the client does not suffer data starvation in his buffer during the video reproduction. So, the overall objective of a VoD service provider is to provide a better Quality of Service (QoS). Some issues related to QoS are-efficient use of bandwidth, providing better throughput etc.One of the important issues is to retrieve the video data from the servers in minimum time and to start the playback of the video at client side with a minimum waiting time. The overall time elapsed in retrieving the video data and starting the playback is known as access time. The thesis presents an efficient retrieval strategy for a distributed VoD environment where the basic objective is to minimize the access time by maintaining the presentation continuity at the client side. We have neglected some of the network parameters which may affect the access time, by assuming a high speed network between the servers and the client. The performance of the strategy has been analyzed and is compared with the referred PAR (Play After Retrieval) strategy. Further, the strategy is also analyzed under availability condition which is a more realistic approach

Mobile Content Delivery Network Design and Implementation

In this thesis, a novel concept of Mobile Content Delivery Network is designed and implemented in a real testbed with the target of flexibly adapting the video caching in the cellular network to the users dynamics. New challenges are discussed and practical considerations for wide-scale deployment in next generation cellular networks are drawn

Heterogeneous Cloud Systems Based on Broadband Embedded Computing

Computing systems continue to evolve from homogeneous systems of commodity-based servers within a single data-center towards modern Cloud systems that consist of numerous data-center clusters virtualized at the infrastructure and application layers to provide scalable, cost-effective and elastic services to devices connected over the Internet. There is an emerging trend towards heterogeneous Cloud systems driven from growth in wired as well as wireless devices that incorporate the potential of millions, and soon billions, of embedded devices enabling new forms of computation and service delivery. Service providers such as broadband cable operators continue to contribute towards this expansion with growing Cloud system infrastructures combined with deployments of increasingly powerful embedded devices across broadband networks. Broadband networks enable access to service provider Cloud data-centers and the Internet from numerous devices. These include home computers, smart-phones, tablets, game-consoles, sensor-networks, and set-top box devices. With these trends in mind, I propose the concept of broadband embedded computing as the utilization of a broadband network of embedded devices for collective computation in conjunction with centralized Cloud infrastructures. I claim that this form of distributed computing results in a new class of heterogeneous Cloud systems, service delivery and application enablement. To support these claims, I present a collection of research contributions in adapting distributed software platforms that include MPI and MapReduce to support simultaneous application execution across centralized data-center blade servers and resource-constrained embedded devices. Leveraging these contributions, I develop two complete prototype system implementations to demonstrate an architecture for heterogeneous Cloud systems based on broadband embedded computing. Each system is validated by executing experiments with applications taken from bioinformatics and image processing as well as communication and computational benchmarks. This vision, however, is not without challenges. The questions on how to adapt standard distributed computing paradigms such as MPI and MapReduce for implementation on potentially resource-constrained embedded devices, and how to adapt cluster computing runtime environments to enable heterogeneous process execution across millions of devices remain open-ended. This dissertation presents methods to begin addressing these open-ended questions through the development and testing of both experimental broadband embedded computing systems and in-depth characterization of broadband network behavior. I present experimental results and comparative analysis that offer potential solutions for optimal scalability and performance for constructing broadband embedded computing systems. I also present a number of contributions enabling practical implementation of both heterogeneous Cloud systems and novel application services based on broadband embedded computing

Distributed streaming media architecture

The recent trends in content delivery indicate that media distribution is among the fastest growing services over the Internet. The lack of QoS support in the Internet has accelerated the development of content distribution architectures and protocols employing techniques such as caching, mirroring and application layer multicast. Though there have been significant efforts in this direction, the large-scale deployment of such architectures is still a challenging problem. This motivates us to develop a novel architecture for content delivery over the best-effort Internet. Towards achieving this goal, we first identify the key components that build up the end-to-end architecture of a media distribution system and discuss their functionalities. Then, we propose a distributed streaming media architecture that is capable of addressing the requirements of client heterogeneity, scalability, and fault-tolerance, overcoming the deficiencies of traditional streaming media architectures. The proposed architecture is highly suitable for scalable encoding techniques such as Multiple Descriptive Coding and Layered Coding. To evaluate the performance of the proposed architecture, we define several performance metrics and carry out extensive simulation studies. Our studies show that clients experience better quality characteristics in the distributed architecture compared to the single server architecture. The proposed distributed architecture brings up several issues, such as quality adaptation, cache replacement and server fault-tolerance, which need further research