1,666 research outputs found

    Disk-based storage for scalable video

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    Distributed multimedia systems

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    A distributed multimedia system (DMS) is an integrated communication, computing, and information system that enables the processing, management, delivery, and presentation of synchronized multimedia information with quality-of-service guarantees. Multimedia information may include discrete media data, such as text, data, and images, and continuous media data, such as video and audio. Such a system enhances human communications by exploiting both visual and aural senses and provides the ultimate flexibility in work and entertainment, allowing one to collaborate with remote participants, view movies on demand, access on-line digital libraries from the desktop, and so forth. In this paper, we present a technical survey of a DMS. We give an overview of distributed multimedia systems, examine the fundamental concept of digital media, identify the applications, and survey the important enabling technologies.published_or_final_versio

    Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

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    Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

    Resurrection: Rethinking Magnetic Tapes For Cost Efficient Data Preservation

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    With the advent of Big Data technologies-the capacity to store and efficiently process large sets of data, doors of opportunities for developing business intelligence that was previously unknown, has opened. Each phase in the processing of this data requires specialized infrastructures. One such phase, the preservation and archiving of data, has proven its usefulness time and again. Data archives are processed using novel data mining methods to elicit vital data gathered over long periods of time and efficiently audit the growth of a business or an organization. Data preservation is also an important aspect of business processes which helps in avoiding loss of important information due to system failures, human errors and natural calamities. This thesis investigates the need, discusses possibilities and presents a novel, highly cost-effective, unified, long- term storage solution for data. Some of the common processes followed in large-scale data warehousing systems are analyzed for overlooked, inordinate shortcomings and a profitably feasible solution is conceived for them. The gap between the general needs of 'efficient' long-term storage and common, current functionalities is analyzed. An attempt to bridge this gap is made through the use of a hybrid, hierarchical media based, performance enhancing middleware and a monolithic namespace filesystem in a new storage architecture, Tape Cloud. The scope of studies carried out by us involves interpreting the effects of using heterogeneous storage media in terms of operational behavior, average latency of data transactions and power consumption. The results show the advantages of the new storage system by demonstrating the difference in operating costs, personnel costs and total cost of ownership from varied perspectives in a business model.Computer Science, Department o

    The design and implementation of a continuous network file system

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    This thesis presents the design and implementation of Continuous Network File System (CNFS), a file system that provides a framework for developing efficient multimedia servers using Linux operating system. CNFS uses a modular approach for designing multimedia file systems utilizing a user-level technique and off-the-shelf commercial products. Multimedia traffic smoothing techniques and real-time issues are explored for the real implementation work. At client-side, CNFS chooses Userfs, a kernel file system skeleton, as its low-level IPC mechanism. The Userfs allows a file system be implemented in user processes. Thus, the whole development environment is more manageable for future research. At server side, KURT, a real-time extension of Linux, is used to provide QoS support for I/O operations. The technique for using KURT for multimedia system is discussed in detail. A complete prototype and functional system using CNFS is built and the process is described in the thesis. Initial performance measurements of the prototype implementation show CNFS capable of achieving real-time delivery of MPEG-1 file under reasonable system loads

    A DFT-Based Running Time Prediction Algorithm for Web Queries

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    Web search engines are built from components capable of processing large amounts of user queries per second in a distributed way. Among them, the index service computes the topk documents that best match each incoming query by means of a document ranking operation. To achieve high performance, dynamic pruning techniques such as the WAND and BM-WAND algorithms are used to avoid fully processing all of the documents related to a query during the ranking operation. Additionally, the index service distributes the ranking operations among clusters of processors wherein in each processor multi-threading is applied to speed up query solution. In this scenario, a query running time prediction algorithm has practical applications in the efficient assignment of processors and threads to incoming queries. We propose a prediction algorithm for the WAND and BM-WAND algorithms. We experimentally show that our proposal is able to achieve accurate prediction results while significantly reducing execution time and memory consumption as compared against an alternative prediction algorithm. Our proposal applies the discrete Fourier transform (DFT) to represent key features affecting query running time whereas the resulting vectors are used to train a feed-forward neural network with back-propagation.Fil: Rojas, Oscar. Universidad de Santiago de Chile; ChileFil: Gil Costa, Graciela Verónica. Universidad Nacional de San Luis. Facultad de Ciencias Físico- Matemáticas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis; ArgentinaFil: Marín, Mauricio. Universidad de Chile; Chil

    Quantum-enhanced imaging with SPAD array cameras

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    (English) Entangled photon pairs can enhance optical imaging capabilities. Phase imaging allows detecting fine detail of transparent samples without potentially invasive fluorescent labelling, and here entanglement enables a higher signal-to-noise ratio (SNR) than possible with only classical light. Spatial correlations from spontaneous parametric down conversion (SPDC) photon pair sources can also be used to increase spatial resolution and robustness to noise and aberrations in imperfect optical systems. Quantum imaging therefore represents a powerful approach to push imaging science beyond its current limits. Until recently, the principal barrier to implementing useful quantum imaging schemes based on entangled photons has been technological, as scalable image sensors capable of multi-photon imaging were unavailable. However, this situation has changed with the development of single photon avalanche diode (SPAD) array cameras, as well as efficient high brightness entangled photon pair sources based on SPDC. These advances have led to the required components now approaching relative technological maturity, opening the window towards engineering useful and scalable systems that exploit entanglement in order to improve optical imaging. In this thesis, we show the development of a quantum imaging platform able to perform practical and fast spatially resolved multi-photon coincidence imaging with high SNR. Special focus is placed on wide-field entanglement-enhanced phase imaging capability, in order to extend experimental sensitivity beyond limits imposed by classical light. The main components of our platform are: sources of hyper-entangled photon pairs, a large field-of-view optical imaging system with phase measurement capabilities, and coincidence imaging using SPAD array cameras. More specifically, the thesis describes: •The first realization of a wide-field entanglement-enhanced phase imager. Wide-field here refers to the ability to acquire images across the entire field-of-view simultaneously (i.e. without need for pixel-to-pixel scanning, sometimes also called full-field). Quantum-enabled super-sensitivity in phase imaging beyond the capability of equivalent classical measurement is demonstrated by careful experimental noise and resource analysis methods. Our system’s capabilities were tested through several sample measurements corresponding to use cases with real-world relevance, including nanometre-scale feature step heights in transparent material, biomedical protein microarrays, as well as birefringent phase samples. •The development of general experimental and numerical tools to calculate photon pair coincidence images and videos from SPAD array cameras, with photon-counting and time-tagging readout modalities, as well as the retrieval of phase images resulting from multi-photon entanglement interference, by adapting techniques from interferometry and holography. We performed also a detailed study and optimization of the influence of different experimental parameters resulting image quality factors. •The evolution and optimization of our system towards real-time quantum imaging capability. Acquisition speed is a key element of usefulness, and in this thesis we integrate, first, a visible-wavelength entangled photon source, and second, a novel time-tagging SPAD array camera. The resulting entanglement-enabled imager presents an improvement by at least four orders of magnitude in measurement speed compared to previous state-of-the-art demonstrations, resulting in the ability to record ~Hz frame rate entangled photon pair coincidence videos. We show that this system, besides phase imaging, has additional applications in the form of real-time entangled state fidelity monitoring, and real-time point spread function characterization of optical systems, which has important applicability to adaptive optical imaging.(Español) Los pares de fotones entrelazados pueden mejorar la capacidad de obtención de imágenes. La formación de imágenes de fase permite detectar detalles de muestras transparentes con alta precisión y sin necesitar marcas fluorescentes potencialmente invasivas. Además, el entrelazamiento permite una mayor relación señal-ruido (SNR, por sus siglas en inglés) de la que es posible utilizando luz clásica. Las correlaciones espaciales de las fuentes de pares de fotones basadas en conversión paramétrica descendente espontánea (SPDC, por sus siglas en inglés) también pueden ser empleadas para aumentar la resolución espacial, y la robustez frente al ruido y a las aberraciones. Por tanto, las técnicas de captación de imagen cuántica son una potente estrategia para impulsar el campo de la ciencia de la fotografía especializada más allá de sus límites actuales. La mayor barrera en la implementación de esquemas de captación de imágenes cuánticas basadas en fotones entrelazados es principalmente tecnológica, al carecer de sensores de imagen escalables capaces de detectar imágenes multifotónicas. No obstante, el desarrollo de cámaras de matriz de fotodiodos de avalancha de fotón único (SPAD, por sus siglas en inglés), y de fuentes de pares de fotones entrelazados de alta eficiencia y brillo, basadas en SPDC, ha cambiado el panorama actual. Estos avances han permitido que los componentes necesarios alcancen una relativa madurez tecnológica, lo que abre una ventana de oportunidad para la ingeniería de sistemas útiles que aprovechan el entrelazamiento para mejorar la imagen óptica. En esta tesis, mostramos el desarrollo de una plataforma de captación de imágenes cuántica práctica y rápida, capaz de generar imágenes mediante el uso de coincidencias multifotónicas. Principalmente, nos centramos en la capacidad de formar imágenes de fase de campo amplio, mejoradas por entrelazamiento. Los componentes principales de nuestra plataforma son: fuentes de pares de fotones hiperentrelazados, un sistema óptico de imagen con un gran campo de visión y capacidad de medición de fase, y formación de imagen mediante la detección en coincidencias utilizando cámaras SPAD. Específicamente, la tesis describe: - La primera realización de un sistema de captación de imágenes de fase en configuración de campo amplio mejorado por entrelazamiento. Utilizando métodos de análisis del ruido y de los recursos, se logró demostrar la supersensibilidad en la medición de fase facilitada por iluminación con luz cuántica. Las capacidades de nuestro sistema se probaron con medidas correspondientes a ejemplos del mundo real, por ejemplo, midiendo microarreglos ultrafinos (grosor de nm) en materiales transparentes, muestras biomédicas de microarrays de proteínas, y de fase birrefringente. - El desarrollo de herramientas numéricas y experimentales generales para calcular imágenes y vídeos de coincidencias de pares de fotones con cámaras SPAD, con modos de lectura de conteo de fotones y etiquetado de tiempo. Además, se desarrolló la recuperación de imágenes de fase del entrelazamiento, adaptando técnicas de interferometría y holografía. Asimismo, se realizó un estudio detallado sobre la influencia de diferentes parámetros experimentales en los factores de calidad de imagen. La evolución y optimización de nuestro sistema hacia la formación de imágenes cuánticas en tiempo real. Se integró primero una fuente de fotones entrelazados de longitud de onda visible y, seguidamente, una nueva cámara SPAD con marcado temporal. El sistema resultante presenta una mejora de al menos cuatro órdenes de magnitud en la velocidad de medición en comparación con otras demostraciones. Esto confiere al sistema la capacidad de grabar vídeos de coincidencias de pares de fotones entrelazados con una tasa de fotogramas de Hz. Este sistema, además de medir la fase, tiene aplicaciones para monitorizar tanto la fidelidad de estados de entrelazamiento como la caracterización de la función de dispersión de punto.Postprint (published version
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