Operating-system support for distributed multimedia

Multimedia applications place new demands upon processors, networks and operating systems. While some network designers, through ATM for example, have considered revolutionary approaches to supporting multimedia, the same cannot be said for operating systems designers. Most work is evolutionary in nature, attempting to identify additional features that can be added to existing systems to support multimedia. Here we describe the Pegasus project's attempt to build an integrated hardware and operating system environment from\ud the ground up specifically targeted towards multimedia

A Prototype Adaptive Optics Real-Time Control Architecture for Extremely Large Telescopes using Many-Core CPUs

A proposed solution to the increased computational demands of Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control (RTC) using many-core CPU technologies is presented. Due to the nearly 4x increase in primary aperture diameter the next generation of 30-40m class ELTs will require much greater computational power than the current 10m class of telescopes. The computational demands of AO RTC scale to the fourth power of telescope diameter to maintain the spatial sampling required for adequate atmospheric correction. The Intel Xeon Phi is a standard socketed CPU processor which combines many (450GB/s) on-chip high bandwidth memory, properties which are perfectly suited to the highly parallelisable and memory bandwidth intensive workloads of ELT-scale AO RTC. Performance of CPU-based RTC software is analysed and compared for the single conjugate, multi conjugate and laser tomographic types of AO operating on the Xeon Phi and other many-core CPU solutions. This report concludes with an investigation into the potential performance of the CPU-based AO RTC software for the proposed instruments of the next generation Extremely Large Telescope (ELT) and the Thirty Meter Telescope (TMT) and also for some high order AO systems at current observatories

A Parallel implementation of an mpeg-2 encoder using message-passing

The days of film are waning as digital cameras and digital video cameras are becoming commonplace. Uncompressed digital video can consume large amounts of space, making it cumbersome to store efficiently. A method of video compression was developed by the Motion Pictures Expert Group (MPEG), and is now an international standard with the International Organization for Standardization (ISO). This thesis deals with the MPEG-2 Video standard, ISO/IEC 13818-2 [2]. The goal of this thesis is to explore the applications of MPEG-2 encoding in a parallel processing paradigm. To achieve this, a sequential MPEG-2 software encoder was obtained from the MPEG Software Simulation Group (MSSG) [18] and modified to be run, in parallel, on a cluster of single-processor Linux workstations using the Message Passing Interface (MPI) [11, 10, 3]. A multi-threaded pipeline of the encoding process was created using Pthreads [6]. The resulting pipelined parallel encoder has been shown to produce compliant elementary MPEG-2 bitstreams for progressive video sequences. Results of simulation showed that the parallel encoder always performed better than the sequential version as the number of processors scaled. However, it did not exhibit the ideal linear speedup that all parallel programs aim to achieve. This is due to the program executing on a set of resources not ideal for the multi-threaded pipeline. The ensuing chapters will provide the motivation for this work, and an overview of MPEG in addition to parallel processing and programming. Also forthcoming will be how it was achieved and the results produced. Supplementary applications of this work will also be discussed

Acceleration of stereo-matching on multi-core CPU and GPU

This paper presents an accelerated version of a dense stereo-correspondence algorithm for two different parallelism enabled architectures, multi-core CPU and GPU. The algorithm is part of the vision system developed for a binocular robot-head in the context of the CloPeMa 1 research project. This research project focuses on the conception of a new clothes folding robot with real-time and high resolution requirements for the vision system. The performance analysis shows that the parallelised stereo-matching algorithm has been significantly accelerated, maintaining 12x and 176x speed-up respectively for multi-core CPU and GPU, compared with non-SIMD singlethread CPU. To analyse the origin of the speed-up and gain deeper understanding about the choice of the optimal hardware, the algorithm was broken into key sub-tasks and the performance was tested for four different hardware architectures

the event driven software library for yarp with algorithms and icub applications

Event-driven (ED) cameras are an emerging technology that sample the visual signal based on changes in the signal magnitude, rather than at a fixed-rate over time. The change in paradigm results in a camera with a lower latency, that uses less power, has reduced bandwidth, and higher dynamic range. Such cameras offer many potential advantages for on-line, autonomous, robots; however the sensor data does not directly integrate with current "image-based" frameworks and software libraries. The iCub robot uses Yet Another Robot Platform (YARP) as middleware to provide modular processing and connectivity to sensors and actuators. This paper introduces a library that incorporates an event-based framework into the YARP architecture, allowing event cameras to be used with the iCub (and other YARP-based) robots. We describe the philosophy and methods for structuring events to facilitate processing, while maintaining low-latency and real-time operation. We also describe several processing modules made available open-source, and three example demonstrations that can be run on the neuromorphic iCub

Design Of Computer Vision Systems For Optimizing The Threat Detection Accuracy

This dissertation considers computer vision (CV) systems in which a central monitoring station receives and analyzes the video streams captured and delivered wirelessly by multiple cameras. It addresses how the bandwidth can be allocated to various cameras by presenting a cross-layer solution that optimizes the overall detection or recognition accuracy. The dissertation presents and develops a real CV system and subsequently provides a detailed experimental analysis of cross-layer optimization. Other unique features of the developed solution include employing the popular HTTP streaming approach, utilizing homogeneous cameras as well as heterogeneous ones with varying capabilities and limitations, and including a new algorithm for estimating the effective medium airtime. The results show that the proposed solution significantly improves the CV accuracy. Additionally, the dissertation features an improved neural network system for object detection. The proposed system considers inherent video characteristics and employs different motion detection and clustering algorithms to focus on the areas of importance in consecutive frames, allowing the system to dynamically and efficiently distribute the detection task among multiple deployments of object detection neural networks. Our experimental results indicate that our proposed method can enhance the mAP (mean average precision), execution time, and required data transmissions to object detection networks. Finally, as recognizing an activity provides significant automation prospects in CV systems, the dissertation presents an efficient activity-detection recurrent neural network that utilizes fast pose/limbs estimation approaches. By combining object detection with pose estimation, the domain of activity detection is shifted from a volume of RGB (Red, Green, and Blue) pixel values to a time-series of relatively small one-dimensional arrays, thereby allowing the activity detection system to take advantage of highly capable neural networks that have been trained on large GPU clusters for thousands of hours. Consequently, capable activity detection systems with considerably fewer training sets and processing hours can be built

Overlay virtualized wireless sensor networks for application in industrial internet of things : a review

Abstract: In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field