Patrick McDonagh

An Evaluation of Parameterized Gradient Based Routing With QoE Monitoring for Multiple IPTV Providers

Future communication networks will be faced with increasing and variable traffic demand, due largely to various services introduced on the Internet. One particular service that will greatly impact resource management of future communication networks is IPTV, which aims to provide users with a multitude of multimedia services (e.g. HD and SD) for both live and on demand streaming. The impact of this will be higher, when we consider multiple IPTV services overlaid on the same network. In this paper we propose a resource management scheme for a network provider that supports multiple IPTV providers. The proposed solution incorporates a new distributed routing mechanism in the underlying network that incorporates QoE monitoring. Through this monitoring process, network providers are able to provide timely updates of quality of flows for each IPTV provider. Simulation work has been conducted to validate the efficiency of the proposed solution in comparison to standard approaches.

Enabling IPTV Service Assurance Using OpenFlow

One difficulty facing Internet Protocol Television (IPTV) service providers is the issue of monitoring and managing their service delivery network. An in-depth monitoring regime is required, which performs measurements within different networking devices. When network conditions deteriorate to the point where they could disrupt IPTV services, Network Operators (NOs) can use the measurements as a basis to reconfigure the network with minimal delay. OpenFlow (OF) presents a potential solution to this problem as it provides vendor-neutral access to the packet forwarding interface of the different hardware device types. This work investigates how OF can leverage video packet inspection measurements taken from within the IPTV service delivery network and combine these with OF statistics to make decisions regarding routing in order to assure service quality.

Integration of QoS Metrics, Rules and Semantic Uplift for Advanced IPTV Monitoring

Abstract Increasing and variable traffic demands due to triple play services pose significant Internet Protocol Television (IPTV) resource management challenges for service providers. Managing subscriber expectations via consolidated IPTV quality reporting will play a crucial role in guaranteeing return-on-investment for players in the increasingly competitive IPTV delivery ecosystem. We propose a fault diagnosis and problem isolation solution that addresses the IPTV monitoring challenge and recommends problem-specific remedial action. IPTV delivery-specific metrics are collected at various points in the delivery topology, the residential gateway and the Digital Subscriber Line Access Multiplexer through to the video Head-End. They are then pre-processed using new metric rules. A semantic uplift engine takes these raw metric logs; it then transforms them into World Wide Web Consortium’s standard Resource Description Framework for knowledge representation and annotates them with expert knowledge from the IPTV domain. This system is then integrated with a monitoring visualization framework that displays monitoring events, alarms, and recommends solutions. A suite of IPTV fault scenarios is presented and used to evaluate the feasibility of the solution. We demonstrate that professional service providers can provide timely reports on the quality of IPTV service delivery using this system.

Experience of developing an openflow SDN prototype for managing IPTV networks

IPTV is a method of delivering TV content to endusers that is growing in popularity. It is a paid service, hence the implications of poor video quality may ultimately be a loss of revenue for the provider. Consequently, it is vital to provide service monitoring and reconfiguration mechanisms to ensure quality requirements set out in service level agreements are upheld. This paper describes our experience of building an IPTV Software Defined Network testbed that can be used to develop and validate new approaches for service assurance in IPTV networks. The testbed is modular and many of the concepts detailed in this tutorial may be applied to the management of other end-to-end services.

Toward Deployable Methods for Assessment of Quality for Scalable IPTV Services

Scalable video coding (H.264 SVC) is an attractive option for video service providers due to its ability to adapt a videos bitstream at the server to suit different network conditions and device characteristics. Lowering a videos bitrate can be achieved through reductions in frame rate, spatial resolution, and/or by increasing the quantization levels applied to the video sequence. In this paper, we first evaluate the effects of such scalability using some full-reference and no-reference video quality metrics, namely PSNR, SSIM, blocking, and blurring. No-reference metrics have the ability to capture the degradation in video quality caused by employing scalability in one or more dimensions. We study if conclusions drawn in previous works, which are based on well-known test video content, hold true for real-world broadcast content. We then discuss how, using these results for a particular content type, the use of no-reference metrics can be enabled in place of, or to supplement, existing widely used full-reference quality assessment metrics. We conduct an experimental analysis by transmitting video encoded at different scalability points over a lossy network to ascertain the effect of loss when scalability is employed in one or more dimensions. We analyze these results using a reduced reference metric called delta-blocking, which can detect visual damage of frames that causes a decrease in a users quality of experience when perceived by the user. If the levels of packet loss are excessively high, this can lead the decoder to drop some video frames. To combat this type of frame loss, we propose a simple windowing algorithm that can automatically re-align the corresponding values for reduced-reference comparison, allowing for video quality monitoring to continue.

Can Road Traffic Volume Information Improve Partitioning for Distributed SUMO

Microscopic vehicular simulations can be computationally intensive due to the sheer size of the road network and number of vehicles. One solution is to parallelize the simulation through distribution and concurrent execution of the scenario being simulated. To enable distributed simulation of an area, the partitioning of the map into different areas for parallel execution on different nodes is required. How the map is partitioned is also a critical factor for distributed simulation, as a poor partitioning can lead to a communication overhead and/or an imbalance of workload among the computing nodes. In this paper, we ask: Can traffic volume information improve the classical structural partitioning algorithms? In the context of improving distributed simulation in SUMO, we propose a modification to three existing mechanisms for road network partitioning, SParTSim, Smart Quadtrees and Quadtrees, with the aim of creating more balanced partitions (in terms of workload) derived from traffic volume data.

Modeling Mobility with Open Data

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing modeling mobility with open data as the reading material.

Determination of bit-rate adaptation thresholds for the opus codec for VoIP services

In this paper, we present an experimental evaluation of the recently standardized Opus codec used in a VoIP context. Opus operates in both narrow and wideband modes, similar to Adaptive Multi-Rate (AMR). Through the use of the Wideband Perceptual Evaluation of Speech Quality (WB-PESQ) metric, we have conducted an extensive set of experiments using multiple audio samples encoded at different bit-rates, to investigate the impact of packet loss on resulting speech quality. Using these results, fitting functions for each bit-rate were computed to provide a straightforward manner of evaluating speech quality when given a specified packet loss rate. Using ns-2, a simulation analysis was conducted to evaluate the effect of background traffic on transmitted Opus streams. We observed that, when using different levels of background traffic, the observed packet loss rates varied heavily depending on the stream bit-rate. By correlating this information with the fitting functions derived previously, we were able to define switching thresholds. These are points where the speech quality of a lower bit-rate stream is greater than that of a higher bit-rate stream for the same levels of link bandwidth saturation.

Micro Analysis of Urban Vehicular Data for Enhanced Information Services for Commuters

The purpose of this paper is to highlight the utility of publicly released urban data-sets and, more specifically, to detail how our analysis was undertaken and to demonstrate the interesting insights regarding vehicular traffic that can be gained from this analysis. This paper uses a data-set provided by Dublin City Council from their Travel-time Reporting and Integrated Performance System (TRIPS). Data from all 45 routes covered by TRIPS was continually collected over the course of a number of months for analysis. From these routes, 4 were selected for detailed analysis. It can be observed that while the routes themselves exhibit some levels of self- similarity, when compared to each other, in some cases their behaviors are distinct. These behaviors are assessed from a number of different aspects to gain insights. Finally, to highlight how data related to vehicular traffic can be used to aid the public, an outline of an application which provides recommendations to commuters is provided. The purpose of this application is to utilise the previously discussed data and analysis to help minimise an individuals commuting time.