Last year, the U.S. Army Yuma Proving Ground (YPG) faced a short suspense requirement to instrument an Apache's Ethernet bus. YPG was able to implement an effective method to satisfy this requirement; however, more capable and effective methodologies could not be developed and utilized due to time constraints. While continuing to support ongoing Apache testing, YPG is working to implement more efficient methods to capture and utilize the Ethernet data. This paper will discuss YPG’s initial implementation and the follow-on efforts being pursued.

Thanks to the advancement of the modern computer simulation systems, many scientific applications generate, and require manipulation of large volumes of data. Scientific exploration substantially relies on effective and accurate data analysis. The shear size of the generated data, however, imposes big challenges in the process of analyzing the system. In this dissertation we propose novel techniques as well as using some known designs in a novel way in order to improve scientific data analysis. We develop an efficient method to compute an analytical query called spatial distance histogram (SDH). Special heuristics are exploited to process SDH efficiently and accurately. We further develop a mathematical model to analyze the mechanism leading to errors. This gives rise to a new approximate algorithm with improved time/accuracy tradeoff. Known MS analysis systems follow a pull-based design, where the executed queries mandate the data needed on their part. Such a design introduces redundant and high I/O traffic as well as cpu/data latency. To remedy such issues, we design and implement a push-based system, which uses a sequential scan-based I/O framework that pushes the loaded data to a number of pre-programmed queries. The efficiency of the proposed system as well as the approximate SDH algorithms is backed by the results of extensive experiments on MS generated data.

In this paper we aim to delve deeper into the film industry and how their approach to streaming services such as Netflix might be the solution to the problems with piracy (people downloading illegally instead of paying for the products) - but before they can change the mindset of people, they have to overcome some issues that might make it hard for the film industry to adapt a fully functionable streaming sollution in the veins of Spotify. To come up with some conclusions regarding this matter, we focused our study on the consumers rather than the industry in order to get a better understanding about what the consumers think about the streaming services of film that are offered today. We used both surveys and interviews in order to gather information regarding the consumers thoughts on how the landscape of film distribution has evolved to a point where Video-on-Demand offers the opportunity to watch movies and TV-series whereever and whenever they want. Our research shows that the majority of consumers are willing to pay for streaming services of film and hold the new technology in high regard. However, the concensus among the consumers that were involved in our study shows that the streaming services offered today have to evolve even further in the future before it can fully work as a substitute for illegal downloading. The film industry has to overcome the problem with illegal downloading, expand their library of movies to give more value for the subscription money and above all continue to develop their streaming services by listening to what the consumers want.

Cette thèse revisite les relations entre les processus attentionnels visuels et la perception de qualité. Nous nous intéressons à la perception de dégradation dans des séquences d’images et leur impact sur la perception de qualité. Plutôt qu’un approcha globale, nous travaillons à une échelle spatio temporelle fine, plus adaptée aux décisions des encodeurs vidéo. Deux approches liant attention visuelle et qualité perçue sont explorées. La première, suit une approche classique, de type pondération des distorsions. Ceci est mis en relation avec des scénarios d’usage comme le streaming interactif ou la visualisation de contenus omnidirectionnels. Une seconde approche nous amène à introduire le concept de disruption visuelle (DV) et sa relation avec la perception de qualité. Nous proposons d’abord des techniques permettant d’étudier les saccades résultantes de la DV à partir par de données expérimentales oculométriques. Nous proposons ensuite un modèle computationnel de prédiction de la DV. Une nouvelle mesure objective de qualité est ainsi introduite nommée "Disruption Metric" permettant l’évaluation de la qualité locale de vidéos. Les résultats obtenus trouvent leurs applications dans de nombreux domaines tels que l’évaluation de qualité, la compression, la transmission perpétuellement optimisée de contenus visuel ou le rendu/visualisation foéval. / This thesis revisits the relationship between visual attentional processes and the perception of quality. We mainly focus on the perception of degradation in video sequences and their overall impact on our perception of quality. Rather than a global approach, we work in a very localized spatio-temporal scale, more adapted to the decision-process in video encoders. Two approaches linking visual attention and perceived quality are explored in the thesis. The first follows a classical approach, of the distortion weighting type. This is very useful in certain scenarios such as interactive streaming or visualization of omni-directional content. The second approach leads us to the introduction of the concept of visual disruption(DV), and explore its relation to perceived quality. We first propose techniques for studying the saccades related to DV from experimental oculometric data. Then, a computational model for the prediction of DV is proposed. A new objective measurement of quality is therefore born, which we call the "Disruption Metric" : that allows the evaluation of the local quality of videos. The results obtained, find their applications in many fields such as quality evaluation, compression, perpetually optimized transmission of visual content or foveated rendering / transmission.

No description available.

Task scheduling in operating system area is well known problem on traditional system architectures (NUMA, SMP). However, it does not perform well on emerging many-core architectures, especially on Intel Xeon Phi. We have collected all publicly available information about the Xeon Phi's architecture. After that we have benchmarked the Xeon Phi to find missing information about its architecture. We were especially curious in architecture of cores and memory controllers. These parts are most important while designing scheduler. Based on the measured results we have proposed improvements to scheduling algorithm in the Bobox - experimental streaming system. Powered by TCPDF (www.tcpdf.org)

Task scheduling in operating system area is a well-known problem on traditional system architectures (NUMA, SMP). Unfortunately, it does not perform well on emerging many-core architectures, especially on Intel Xeon Phi. We collected all publicly available information about the architecture of Xeon Phi. After that, we benchmarked the Xeon Phi in order to find the missing information about its architecture. We focused especially on the information about cores and memory controllers. These are the most important parts when designing a scheduler. Based on the results, we proposed improvements for scheduling algorithm in the Bobox (an experimental streaming system). However, we found that the biggest problem is not in the scheduling algorithm, but in the design of operators' parallelization. Therefore, we proposed improvements to the parallelization and tested one of the proposals.

Modern simulation systems generate big amount of data, which consequently has to be analyzed in a timely fashion. Traditional database management systems follow principle of pulling the needed data, processing it, and then returning the results. This approach is then optimized by means of caching, storing in different structures, or doing some sacrifices on precision of the results to make it faster. When it comes to the point of doing various queries that require analysis of the whole data, this design has the following disadvantages: considerable overhead on traditional disk random I/O framework while reading from the simulation output files and low throughput of the data that consequently results in long latency, and, if there was any indexing to optimize selections, overhead of storing those becomes too big, too. Beside it, indexing will also cause delay during write operations and since most of the queries work with the entire data sets, indexing loses its point. There is a new approach to this problem – Push-based System for Molecular Simulation Data Analysis for processing network of queries proposed in the previous paper and its primary steps are: i) it uses traditional scan-based I/O framework to load the data from files to the main memory and then ii) the data is pushed through a network of queries which consequently filters the data and collect all the needed information which increases efficiency and data throughput. It has a considerable advantage in analysis of molecular simulation data, because it normally involves all the data sets to be processed by the queries. In this paper, we propose improved version of Push-based System for Molecular Simulation Data Analysis. Its major difference with the previous design is usage of GPU for the actual processing part of the data flow. Using the same scan-based I/O framework the data is pushed through the network of queries which are processed by GPU, and due to the nature of science simulation data, this gives a big advantage for processing it faster and easier (it will be explained more in later sections). In the old approach there were some custom data structures such as quad-tree for calculation of histograms to make the processing faster and those involved loss of data and some expectations from the data nature, too. In the new approach due to high performance of GPU processing and its nature, custom data structures were not even needed much, though it didn’t bear any loss in precision and performance.

The transmitting of video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling effect and the path length growth severely impair the performance of multipath schemes. In this thesis, the current research status about video streaming over VANETs as well as multipath transmissions are reviewed. With the demand to discover a more suitable solution, we propose the Location-Aware Multipath Video Streaming (LIAITHON+) protocol to address video streaming over urban VANETs. LIAITHON+ uses location information to discover relatively short paths with minimal route coupling effect. The performance results have shown it outperforms the underlying single path solution as well as the node-disjoint multipath solution. In addition, the impact of added redundancy on the multipath solution is investigated through LIAITHON+. According to the results, added redundancy has a different impact depending on the data rate.

With the rapid development in the areas of mobile manufacturing and multimedia communications, there is an increasing demand for Networked Virtual Environment (NVE) applications, such as Augmented Reality (AR), virtual walk-throughs, and massively multiplayer online games (MMOGs), on hand-held devices. Unfortunately, downloading and rendering a complex 3D scene is very computationally intensive and is not compatible with current mobile hardware specifications nor with available wireless bandwidth. Existing NVE applications deploy client/server based 3D streaming over thin mobile devices, which suffer from single point of failure, latency, and scalability issues. To address these issues, image-based rendering (IBR) and cloud-based 3D streaming have been introduced. The former introduces visual artifacts that reduce, and usually cancel, the realistic behaviors of the Virtual Environment (VE) application, while the latter is considered very expensive to implement. Peer-to-peer (P2P) 3D streaming is promising and affordable, but it has to tackle issues in object discovery and selection as well as content provider strategies. Distributing VE content over a mobile ad-hoc network (MANET) makes the system difficult to update due to the dynamic nature of the mobile clients. In order to tackle these issues, we came up with a novel protocol that combines the pros of both central and distributed approaches. Our proposed hybrid protocol, called OCTET, enables 3D scene streaming over thin devices in a way that can cope with current mobile hardware capabilities and mitigate the challenges of client/server and P2P 3D streaming. In fact, OCTET provides strategies that select, prioritize, and deliver only those objects that contribute to the user’s visible scene. OCTET is implemented using the "ns-2" simulation environment, and extensive experiments have clearly demonstrated significant achievements in mobile resource utilization, throughput, and system scalability.