Management of Digital Video Broadcasting Services in Open Delivery Platforms

The future of Digital Video Broadcasting (DVB) is moving towards solutions offering an efficient way of carrying interactive IP multimedia services over digital terrestrial broadcasting networks to handheld terminals. One of the most promising technologies is Digital Video Broadcasting-Handheld (DVB-H), at present under standardisation. Services deployed via this type of DVB technologies should enjoy reliability comparable to TV services and high quality standards. However, the market at present does not provide effective and economical solutions for the deployment of such services over multi-domain IP networks, due to their high level of unreliability. This paper focuses on service management, service level agreement (SLA) and network performance requirements of DVB-H services. Experimental results are presented concerning QoS sensitivity to network performance of DVB-H services delivered over a multi-domain IP network. Moreover, a solution for efficient and cost effective service management via QoS monitoring and control and network SLA design is proposed. The solution gives DVB-H operators the possibility of fully managing service QoS without being tied to third party operators

Phase-sensitive imaging of the outer retina using optical coherence tomography and adaptive optics

The cone photoreceptor’s outer segment (OS) experiences changes in optical path length, both in response to visible stimuli and as a matter of its daily course of renewal and shedding. These changes are of interest, to quantify function in healthy cells and assess dysfunction in diseased ones. While optical coherence tomography (OCT), combined with adaptive optics (AO), has permitted unprecedented three-dimensional resolution in the living retina, it has not generally been able to measure these OS dynamics, whose scale is smaller than OCT’s axial resolution of a few microns. A possible solution is to take advantage of the phase information encoded in the OCT signal. Phase-sensitive implementations of spectral-domain optical coherence tomography (SD-OCT) have been demonstrated, capable of resolving sample axial displacements much smaller than the imaging wavelength, but these have been limited to ex vivo samples. In this paper we present a novel technique for retrieving phase information from OCT volumes of the outer retina. The key component of our technique is quantification of phase differences within the retina. We provide a quantitative analysis of such phase information and show that–when combined with appropriate methods for filtering and unwrapping–it can improve the sensitivity to OS length change by more than an order of magnitude, down to 45 nm, slightly thicker than a single OS disc. We further show that phase sensitivity drops off with retinal eccentricity, and that the best location for phase imaging is close to the fovea. We apply the technique to the measurement of sub-resolution changes in the OS over matters of hours. Using custom software for registration and tracking, these microscopic changes are monitored in hundreds of cones over time. In two subjects, the OS was found to have average elongation rates of 150 nm/hr, values which agree with our previous findings

QoS-aware mechanisms for improving cost-efficiency of datacenters

Warehouse Scale Computers (WSCs) promise high cost-efficiency by amortizing power, cooling, and management overheads. WSCs today host a large variety of jobs with two broad performance requirements categories: latency-critical (LC) and best-effort (BE). Ideally, to fully utilize all hardware resources, WSC operators can simply fill all the nodes with computing jobs. Unfortunately, because colocated jobs contend for shared resources, systems with high loads often experience performance degradation, which negatively impacts the Quality of Service (QoS) for LC jobs. In fact, service providers usually over-provision resources to avoid any interference with LC jobs, leading to significant resource inefficiencies. In this dissertation, I explore opportunities across different system-abstraction layers to improve the cost-efficiency of dataceters by increasing resource utilization of WSCs with little or no impact on the performance of LC jobs. The dissertation has three main components. First, I explore opportunities to improve the throughput of multicore systems by reducing the performance variation of LC jobs. The main insight is that by reshaping the latency distribution curve, performance headroom of LC jobs can be effectively converted to improved BE throughput. I develop, implement, and evaluate a runtime system that achieves this goal with existing hardware. I leverage the cache partitioning, per-core frequency scaling, and thread masking of server processors. Evaluation results show the proposed solution enables 30% higher system throughput compared to solutions proposed in prior works while maintaining at least as good QoS for LC jobs. Second, I study resource contention in near-future heterogeneous memory architectures (HMA). This study is motivated by recent developments in non-volatile memory (NVM) technologies, which enable higher storage density at the cost of same performance. To understand the performance and QoS impact of HMAs, I design and implement a performance emulator in the Linux kernel that runs unmodified workloads with high accuracy, low overhead, and complete transparency. I further propose and evaluate multiple data and resource management QoS mechanisms, such as locality-aware page admission, occupancy management, and write buffer jailing. Third, I focus on accelerated machine learning (ML) systems. By profiling the performance of production workloads and accelerators, I show that accelerated ML tasks are highly sensitive to main memory interference due to fine-grained interaction between CPU and accelerator tasks. As a result, memory resource contention can significantly decreases the performance and efficiency gains of accelerators. I propose a runtime system that leverages existing hardware capabilities and show 17% higher system efficiency compared to previous approaches. This study further exposes opportunities for future processor architecturesElectrical and Computer Engineerin

Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Evaluation of Wirelessly Transmitted Video Quality Using a Modular Fuzzy Logic System

Video transmission over wireless computer networks is increasingly popular as new applications emerge and wireless networks become more widespread and reliable. An ability to quantify the quality of a video transmitted using a wireless computer network is important for determining network performance and its improvement. The process requires analysing the images making up the video from the point of view of noise and associated distortion as well as traffic parameters represented by packet delay, jitter and loss. In this study a modular fuzzy logic based system was developed to quantify the quality of video transmission over a wireless computer network. Peak signal to noise ratio, structural similarity index and image difference were used to represent the user's quality of experience (QoE) while packet delay, jitter and percentage packet loss ratio were used to represent traffic related quality of service (QoS). An overall measure of the video quality was obtained by combining QoE and QoS values. Systematic sampling was used to reduce the number of images processed and a novel scheme was devised whereby the images were partitioned to more sensitively localize distortions. To further validate the developed system, a subjective test involving 25 participants graded the quality of the received video. The image partitioning significantly improved the video quality evaluation. The subjective test results correlated with the developed fuzzy logic approach. The video quality assessment developed in this study was compared against a method that uses spatial efficient entropic differencing and consistent results were observed. The study indicated that the developed fuzzy logic approaches could accurately determine the quality of a wirelessly transmitted video

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin