This thesis addresses video streaming from smartphone to smartwatch. The main goal of the thesis is to find a way how to handle the limited hardware features of the watch and make video streaming as fast and smooth as possible. A part of this work is focused on implementation of client-server application, which streams video from Android device to Tizen smartwatch over Bluetooth channel.

El objetivo principal del presente trabajo de investigación es demostrar la viabilidad de una plataforma que permite realizar intercambio de ítems, apuestas y visualizar streaming de e-sports en una sola plataforma, llamada Game Now. Gracias a la investigación realizada a hombres y mujeres de 18 a 39 años residente en Lima Metropolitana de los NSE A, B y C pertenecientes a la Población Económicamente Activa, gamers y apostantes en videojuegos, hemos podido detectar que existe una alta aceptación de esta plataforma, pues muchos investigados rescatan que la plataforma les brindaría mayor comodidad. Sin embargo, existe una preocupación constante en la seguridad, pues los usuarios constantemente estarían poniendo en juego su dinero. Por lo tanto, se realizó una planeación estratégica en donde se llevó a cabo el desarrollo del Plan de Operaciones, Plan de Recursos Humanos, Plan de Marketing, Plan Financiero y Plan de Responsabilidad Social Empresarial. En cada uno de ellos se ha contemplado el compromiso de brindar seguridad dentro de la plataforma, como en los costos adquiriendo certificaciones y firmas digitales, así como trabajar con empresas de seguridad en los procesos de cobranza / además del personal capacitado para el desarrollo de la infraestructura, información y seguridad de la plataforma. Como resultado de todo ello, considerando una inversión inicial de S/200, 000 y una proyección de las ventas positivas, el proyecto generaría valor obteniendo utilidades netas de S/26, 319, S/81, 438 y S/151, 493, para el año 2021, 2022 y 2023 respectivamente.

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Vad är det som gör att en miljon människor lägger tid på att streama datorspel? Live streaming har funnits sedan 1920-talet, då i form av musik i hissar. På 1990-talet började hemdatorer utvecklas hårdvarumässigt tillräckligt för att kunna streama film och ljud. Med en kvalitativ enkät publicerad på nätet undersöker vi i den här uppsatsen varför en miljon personer idag väljer att streama när de spelar dator eller tv spel. Resultat vi kommer fram till är ett antal kategorier med olika motiveringar till varför en person väljer att dela med sig av sina spelupplevelser till andra.

In many applications, e.g. urban traffic monitoring, stock trading, and industrial sensor data monitoring, clustering algorithms are applied on data streams in real-time to find current patterns. Here, sliding windows are commonly used as they capture concept drift. Real-time clustering over sliding windows is early detection of continuously evolving clusters as soon as they occur in the stream, which requires efficient maintenance of cluster memberships that change as windows slide. Data stream management systems (DSMSs) provide high-level query languages for searching and analyzing streaming data. In this thesis we extend a DSMS with a real-time data stream clustering framework called Generic 2-phase Continuous Summarization framework (G2CS).  G2CS modularizes data stream clustering by taking as input clustering algorithms which are expressed in terms of a number of functions and indexing structures. G2CS supports real-time clustering by efficient window sliding mechanism and algorithm transparent indexing. A particular challenge for real-time detection of a high number of rapidly evolving clusters is efficiency of window slides for clustering algorithms where deletion of expired data is not supported, e.g. BIRCH. To that end, G2CS includes a novel window maintenance mechanism called Sliding Binary Merge (SBM). To further improve real-time sliding performance, G2CS uses generation-based multi-dimensional indexing where indexing structures suitable for the clustering algorithms can be plugged-in.

Video streaming has become increasingly popular with commercial video streaming applications such as YouTube accounting for a large quantity of Internet traffic. While streaming video is sensitive to bandwidth jitter, a receiver buffer can ameliorate the effects of jitter by adjusting to the difference between the transmission rate and the playback rate. Unfortunately, there are few studies to determine the best size of the receiver buffer for TCP streaming. In this work, we investigate how the buffer size of video streaming applications changes with respect to variation in bandwidth. We model the video streaming system over TCP using simulation to develop our buffering algorithm. We propose using a dynamic client buffer size based on measured bandwidth variation to achieve fewer interruptions in video streaming playback. To evaluate our approach, we implement an application to run experiments comparing our algorithm with the buffer size of commercial video streaming.

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major Telecomunicação). Faculdade de Engenharia. Universidade do Porto. 2010

<p>Streaming applications like multimedia and radar signal processing applications are becoming </p><p>increasingly compute-intensive. To overcome the computational demands new parallel </p><p>architectures are emerging. </p><p> </p><p>The programming tools provided with these architectures require low-level programming, which </p><p>creates a need for a common high-level architecture independent language that can exploit </p><p>parallelism efficiently. One such language is StreamIt, designed around the notions of streams </p><p>and stream transformers, which allows efficient mapping to a variety of architectures. </p><p> </p><p>The overall goal of this master’s thesis is to evaluate the StreamIt language from a </p><p>programmability and portability point of view. An MPD-application has been developed in </p><p>StreamIt, which is executed on the RAW simulator. Furthermore, a code generator is designed to </p><p>compile and execute the application on the XPP simulator. </p><p> </p><p>The conclusions drawn are that StreamIt is easy to learn, but hard to use because of its </p><p>programming paradigm as compared to conventional languages. StreamIt programming involves </p><p>thinking in terms of streams instead of globally accessed memory. The structure of StreamIt </p><p>makes it easy to reuse components and modify the application. The construction of the compiler </p><p>makes it possible to port StreamIt application to various architectures.</p>

<p>Idag finns som alltid behovet att distribuera media. Allt eftersom prestandan för överföring av information i dator-nätverk har ökat har detta blivit möjligt genom streaming, strömmande media. Detta innebär att klienten inte behöver ladda ner hela materialet för att kunna se eller lyssna på det. Allt eftersom kravet på kvalitén av materialet ökar blir kraven på nätverket högre. Precisallt Media AB är ett företagsom sysslar med digital skyltning. För att nå ut med film till sina skyltar som finns i olika butiker och varuhus, schemaläggs och skickas film till en vanlig pc som sköter skylten. Lagring av video sker lokalt, det vill säga materialet som spelas upp på en skylt är lagrat på samma dator som spelar upp det. Detta är ingen effektiv lösning eftersom överföringen av material som sker över Internet måste ske till varje dator som ska spela upp det. Går det att skapa en effektivare lösning genom att använda streaming hos kunden? Och går det att effektivisera distribueringen av media tillkundens nätverk?</p>

Recent studies have shown that, in a sufficiently deep gas-solid fluidized bed of Geldart A particles, gas streaming may occur allowing gas to bypass a large portion of the particle bed. Since this is a newly observed phenomenon in fluidized beds, there is uncertainty and lack of information about the various aspects of the streaming flow. The objective of the current project is to investigate the streaming phenomenon with a combination of experimentation and modeling. In the experimental part, pressure fluctuations as a measure of the fluidized bed hydrodynamics were used to study the influence of different parameters on the behavior of a deep fluidized bed. Pressure fluctuations have been measured at 8 axial locations from 4 to 150 cm above the gas distributor for bed depths and gas velocities ranging from 0.4 to 1.6 m and 0.04 to 0.20 m/s (equal to 10 to 50 times minimum fluidization velocity), respectively. Two particle size distributions with Sauter mean diameters of 48 µm and 84 µm and two distributor plates with differing percentage open area were also tested for each bed depth and gas velocity. Analysis of pressure fluctuations in the time and frequency domains, in combination with visual observations revealed that streaming flow emerges gradually at bed depths greater than 1 m. Increased gas velocity and fines content act to delay the onset of streaming, but can not completely eliminate it over the range of velocities examined. The two different distributor designs had no measurable effect on the streaming flow. The results of this study are provided in the first section of the present report.<p> In order to further investigate the nature of streaming flow, several cases of forced streams and jetting flows were designed and conducted, in addition to the natural streaming flow in deep beds. Results indicated that the natural streaming most closely resembles the imposed stream which not only the imposed stream, but additional gas added through the distributor. The case of jet flows with no additional gas resembles the severe streaming that might happen in very deep beds with the existence of completely non-fluidized regions. Application of supporting jets in addition to the main gas flow could enhance the fluidization quality to some extent, however, not enough to provide a normal fluidization. Wavelet analysis of the pressure fluctuations showed that in deep fluidized beds, bubbling activity with the typical dominant frequency coexist with the streaming flow, with a minor contribution. Wavelet findings suggested that the streaming flow can be considered to form by increasing the relative importance of one available stream of bubble activity with increasing bed depth. The results of this study are provided in the second section of this report. Further study of the streaming flow was undertaken with computational fluid dynamic (CFD) simulation of the deep fluidized bed. CFD simulation of fine Geldart A particles has met with challenges in the open literature and various modifications have been proposed to be able to model fluidized beds of these particles. In the present work, the commercial CFD codes FLUENT and MFIX were initially tested for the modeling of deep fluidized bed of Geldart A particles. However, simulation results did not show any sign of streaming flow in the fluidized bed. Subsequently, the commercial CFD code BARRACUDATM that has been claimed by the developers to be appropriate for this purpose, was tested. Due to the lack of data on the performance of this code, a simple case of modeling a freely bubbling fluidized bed of Geldart A particles was attempted first. For this purpose, four different simulation cases, which included three different numerical grid sizes and two drag models with a realistic particle size distribution were designed and tested. The simulated bed expansion, bubble size distribution, rise velocity and solid fraction were compared with commonly accepted correlations and experimental data from the literature. The results showed a promising predictive capability of the code without the need for modifying the drag model or other constitutive relations of the model. The third section of the report presents the simulation results of this study.<p> The BARRACUDA code was then used for simulating the deep fluidized bed of Geldart A particles. However, similar to the previous CFD codes tested, instead of streaming flow, bubbling fluidization was predicted. Therefore, a phenomenological model was developed to better understand the streaming flow. According to the model results, the stream represents a zone of much lower pressure drop compared to other parts of the bed, which can be a possible reason for the formation and stability of the streaming flow inside the fluidized bed. The model results showed that increasing the bed depth enhances the streaming flow, while increasing the gas velocity improves the uniformity of the bed and decreases the streaming severity. Streaming flow was found to be less severe for larger particle sizes. All of these trends are in conformity with the experimental results. These findings provide the content of the fourth and final section of this report.