Performance and Energy Consumption Characterization and Modeling of Video Decoding on Multi-core Heterogenous SoC and their Applications

To meet the increasing complexity of mobile multimedia applications, the System on Chip (SoC) equipping modern mobile devices integrate powerful heterogeneous processing elements among which General Purpose Processors (GPP), Digital Signal Processors (DSP), hardware accelerator are the most common ones.Due to the ever-growing gap between battery lifetime and hardware/software complexity in addition to application computing power needs, the energy saving issue becomes crucial in the design of such systems. In this context, we propose a study aiming to enhance the understanding of the energy consumption behavior of video decoding on these kinds of systems. Accordingly, an end-to-end methodology for characterizing and modeling the performance and the energy consumption of video decoding on GPP and DSP is proposed. The characterization step is based on an exhaustive experimental methodology for evaluating, at different abstraction levels, the performance and the energy consumption of video decoding. It was achieved on embedded platforms on which were executed a wide range of video decoding configurations. This step highlighted the importance to consider different parameters which may pertain to different abstraction levels in evaluating the overall energy efficiency of a given system. The measurements obtained in this step were used to build empirically performance and energy models for video decoding on both GPP and DSP. The proposed models gave very accurate estimation (R 2 = 97%) of both the performance and the energy consumption of video decoding in terms of a rich set of parameters including the video quality and the processor frequency. Moreover, based on a multi-level characterization and sub-model decomposition approaches, we show how the developed models, unlike classic empirical models, are easily and rapidly generalizable to other platforms.Some possible applications using the developed models, in the context of adaptive video decoding, were proposed. In general, it consists to use the capability of the proposed performance model to predict the decoding time of a given video quality in dimensioning/scheduling the processing resources. Due to the increasing demand on High Definition (HD), the characterization methodology was extended to consider HD video decoding on both parallel multi-cores and hardware video accelerator. This part highlighted the potential of parallelism video decoding to increase the energy efficiency of video decoding and point out some open issues in this domain.Pour répondre à la complexité croissante des applications multimédia mobiles, les systèmes sur puce équipant les appareils mobiles modernes intègrent des unités de calcul puissantes et hétérogène. Parmi ces units de calcul, on peut trouver des processeurs à usage général, des processeur de traitement de signal et des accélérateurs matériels. En raison de l’écart toujours croissant entre la durée de vie des batteries et la demande de plus en plus importante en puissance de calcul, l’économie d’énergie devient un enjeu crucial dans la conception des systèmes mobiles. Cette problématique est accentuée par l’augmentation de la complexité des logiciels et architectures matériels utilisés. Dans ce contexte, nous proposons une étude visant à améliorer la compréhension des considérations énergétiques du décodage vidéo sur ce genre de systèmes. Nous proposerons ainsi une méthodologie pour la caractérisation et la modélisation des performances et de la consommation d’énergie du décodage vidéo, aussi bien sur des processeurs à usage général de type ARM que sur un processeurde traitement de signal. L’étape de caractérisation est basée sur une méthodologie expérimentale pour évaluer de façon exhaustive et à différents niveaux d’abstraction, les performances et la consommation d’énergie du décodage vidéo. Cette caractérisation a été réalisée sur des plates-formes embarquées sur lesquels ont été exécutés un large éventail de configurations du décodage vidéo. Cette étape a souligné l’importance d’examiner différents paramètres qui peuvent se rapporter à différents niveaux d’abstraction dans l’évaluation de l’efficacité énergétique globale d’un système donné. Les mesures obtenues dans cette étape ont été utilisées pour construire empiriquement des modèles de performance et de consommation d’énergie pour le décodage vidéo à la fois sur des processeurs à usage général type ARM et sur un processeur de traitement de signal. Les modèles proposés peuvent estimer avec une grande précision (R 2 = 97%) la performance et la consommation d’énergie de décodage vidéo en fonction d’un nombre de paramètres comprenant la qualité de la vidéo et la fréquence du processeur. En plus, en se basant sur une caractérisation multi-niveaux et une approches de modélisation par décomposition en sous-modèles, nous montrons comment les modèles développés, contrairement aux modèles empiriques classiques, sont facilement et rapidement généralisables à d’autres plates-formes. Nous proposerons également certaines applications possibles des modèles développés, dans le cadre du décodage vidéo adaptatif. En général, cela consiste à exploiter la capacité du modèle de performance proposé pour prédire le temps de décodage d’une qualité vidéo donnée afin de mieux dimensionner les ressources de calculs dans un but de réduire leur consommationd’énergie

Quality of experience and access network traffic management of HTTP adaptive video streaming

The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming

Performance modelling with adaptive hidden Markov models and discriminatory processor sharing queues

In modern computer systems, workload varies at different times and locations. It is important to model the performance of such systems via workload models that are both representative and efficient. For example, model-generated workloads represent realistic system behaviour, especially during peak times, when it is crucial to predict and address performance bottlenecks. In this thesis, we model performance, namely throughput and delay, using adaptive models and discrete queues. Hidden Markov models (HMMs) parsimoniously capture the correlation and burstiness of workloads with spatiotemporal characteristics. By adapting the batch training of standard HMMs to incremental learning, online HMMs act as benchmarks on workloads obtained from live systems (i.e. storage systems and financial markets) and reduce time complexity of the Baum-Welch algorithm. Similarly, by extending HMM capabilities to train on multiple traces simultaneously it follows that workloads of different types are modelled in parallel by a multi-input HMM. Typically, the HMM-generated traces verify the throughput and burstiness of the real data. Applications of adaptive HMMs include predicting user behaviour in social networks and performance-energy measurements in smartphone applications. Equally important is measuring system delay through response times. For example, workloads such as Internet traffic arriving at routers are affected by queueing delays. To meet quality of service needs, queueing delays must be minimised and, hence, it is important to model and predict such queueing delays in an efficient and cost-effective manner. Therefore, we propose a class of discrete, processor-sharing queues for approximating queueing delay as response time distributions, which represent service level agreements at specific spatiotemporal levels. We adapt discrete queues to model job arrivals with distributions given by a Markov-modulated Poisson process (MMPP) and served under discriminatory processor-sharing scheduling. Further, we propose a dynamic strategy of service allocation to minimise delays in UDP traffic flows whilst maximising a utility function.Open Acces

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

On the design of efficient caching systems

Content distribution is currently the prevalent Internet use case, accounting for the majority of global Internet traffic and growing exponentially. There is general consensus that the most effective method to deal with the large amount of content demand is through the deployment of massively distributed caching infrastructures as the means to localise content delivery traffic. Solutions based on caching have been already widely deployed through Content Delivery Networks. Ubiquitous caching is also a fundamental aspect of the emerging Information-Centric Networking paradigm which aims to rethink the current Internet architecture for long term evolution. Distributed content caching systems are expected to grow substantially in the future, in terms of both footprint and traffic carried and, as such, will become substantially more complex and costly. This thesis addresses the problem of designing scalable and cost-effective distributed caching systems that will be able to efficiently support the expected massive growth of content traffic and makes three distinct contributions. First, it produces an extensive theoretical characterisation of sharding, which is a widely used technique to allocate data items to resources of a distributed system according to a hash function. Based on the findings unveiled by this analysis, two systems are designed contributing to the abovementioned objective. The first is a framework and related algorithms for enabling efficient load-balanced content caching. This solution provides qualitative advantages over previously proposed solutions, such as ease of modelling and availability of knobs to fine-tune performance, as well as quantitative advantages, such as 2x increase in cache hit ratio and 19-33% reduction in load imbalance while maintaining comparable latency to other approaches. The second is the design and implementation of a caching node enabling 20 Gbps speeds based on inexpensive commodity hardware. We believe these contributions advance significantly the state of the art in distributed caching systems

Workload Interleaving with Performance Guarantees in Data Centers

In the era of global, large scale data centers residing in clouds, many applications and users share the same pool of resources for the purposes of reducing energy and operating costs, and of improving availability and reliability. Along with the above benefits, resource sharing also introduces performance challenges: when multiple workloads access the same resources concurrently, contention may occur and introduce delays in the performance of individual workloads. Providing performance isolation to individual workloads needs effective management methodologies. The challenges of deriving effective management methodologies lie in finding accurate, robust, compact metrics and models to drive algorithms that can meet different performance objectives while achieving efficient utilization of resources. This dissertation proposes a set of methodologies aiming at solving the challenging performance isolation problem in workload interleaving in data centers, focusing on both storage components and computing components. at the storage node level, we focus on methodologies for better interleaving user traffic with background workloads, such as tasks for improving reliability, availability, and power savings. More specifically, a scheduling policy for background workload based on the statistical characteristics of the system busy periods and a methodology that quantitatively estimates the performance impact of power savings are developed. at the storage cluster level, we consider methodologies on how to efficiently conduct work consolidation and schedule asynchronous updates without violating user performance targets. More specifically, we develop a framework that can estimate beforehand the benefits and overheads of each option in order to automate the process of reaching intelligent consolidation decisions while achieving faster eventual consistency. at the computing node level, we focus on improving workload interleaving at off-the-shelf servers as they are the basic building blocks of large-scale data centers. We develop priority scheduling middleware that employs different policies to schedule background tasks based on the instantaneous resource requirements of the high priority applications running on the server node. Finally, at the computing cluster level, we investigate popular computing frameworks for large-scale data intensive distributed processing, such as MapReduce and its Hadoop implementation. We develop a new Hadoop scheduler called DyScale to exploit capabilities offered by heterogeneous cores in order to achieve a variety of performance objectives

Using Ontologies and Intelligent Systems for Traffic Accident Assistance in Vehicular Environments

A pesar de que las medidas de seguridad en los sistemas de transporte cada vez son mayores, el aumento progresivo del número de vehículos que circulan por las ciudades y carreteras en todo el mundo aumenta, sin duda, la probabilidad de que ocurra un accidente. En este tipo de situaciones, el tiempo de respuesta de los servicios de emergencia es crucial, ya que está demostrado que cuanto menor sea el tiempo transcurrido entre el accidente y la atención hospitalaria de los heridos, mayores son sus probabilidades de supervivencia. Las redes vehiculares permiten la comunicación entre los vehículos, así como la comunicación entre los vehículos y la infraestructura [4], lo que da lugar a una plétora de nuevas aplicaciones y servicios en el entorno vehicular. Centrándonos en las aplicaciones relacionadas con la seguridad vial, mediante este tipo de comunicaciones, los vehículos podrían informar en caso de accidente al resto de vehículos (evitando así colisiones en cadena) y a los servicios de emergencia (dando información precisa y rápida, lo que sin duda facilitaría las tareas de rescate). Uno de los aspectos importantes a determinar sería saber qué información se debe enviar, quién será capaz de recibirla, y cómo actuar una vez recibida. Actualmente los vehículos disponen de una serie de sensores que les permiten obtener información sobre ellos mismos (velocidad, posición, estado de los sistemas de seguridad, número de ocupantes del vehículo, etc.), y sobre su entorno (información meteorológica, estado de la calzada, luminosidad, etc.). En caso de accidente, toda esa información puede ser estructurada y enviada a los servicios de emergencia para que éstos adecúen el rescate a las características específicas y la gravedad del accidente, actuando en consecuencia. Por otro lado, para que la información enviada por los vehículos accidentados pueda llegar correctamente a los servicios de emergencias, es necesario disponer de una infraestructura capaz de dar cobertura a todos los vehículos que circulan por una determinada área. Puesto que la instalación y el mantenimiento de dicha infraestructura conllevan un elevado coste, sería conveniente proponer, implementar y evaluar técnicas consistentes en dar cobertura a todos los vehículos, reduciendo el coste total de la infraestructura. Finalmente, una vez que la información ha sido recibida por las autoridades, es necesario elaborar un plan de actuación eficaz, que permita el rápido rescate de los heridos. Hay que tener en cuenta que, cuando ocurre un accidente de tráfico, el tiempo de personación de los servicios de emergencia en el lugar del accidente puede suponer la diferencia entre que los heridos sobrevivan o fallezcan. Además, es importante conocer si la calle o carretera por la que circulaban los vehículos accidentados ha dejado de ser transitable para el resto de vehículos, y en ese caso, activar los mecanismos necesarios que permitan evitar los atascos asociados. En esta Tesis, se pretende gestionar adecuadamente estas situaciones adversas, distribuyendo el tráfico de manera inteligente para reducir el tiempo de llegada de los servicios de emergencia al lugar del accidente, evitando además posibles atascos.Barrachina Villalba, J. (2014). Using Ontologies and Intelligent Systems for Traffic Accident Assistance in Vehicular Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39004TESI

Secure multi-constrained QoS reliable routing algorithm for vehicular ad hoc networks (VANETs)

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonVehicular Ad hoc Networks (VANETs) are a particular form of wireless network made by vehicles communicating among themselves and with roadside base stations. A wide range of services has been developed for VANETs ranging from safety to infotainment applications. A key requirement for such services is that they are offered with Quality of Service (QoS) guarantees in terms of service reliability and availability. Furthermore, due to the openness of VANET’s wireless channels to both internal and external attacks, the application of security mechanisms is mandatory to protect the offered QoS guarantees. QoS routing plays an essential role in identifying routes that meet the QoS requirements of the offered service over VANETs. However, searching for feasible routes subject to multiple QoS constraints is in general an NP-hard problem. Moreover, routing reliability needs to be given special attention as communication links frequently break in VANETs. To date, most existing QoS routing algorithms are designed for stable networks without considering the security of the routing process. Therefore, they are not suitable for applications in VANETs. In this thesis, the above issues are addressed firstly by developing a link reliability model based on the topological and mathematical properties of vehicular movements and velocities. Evolving graph theory is then utilised to model the VANET communication graph and integrate the developed link reliability model into it. Based on the resulting extended evolving graph model, the most reliable route in the network is picked. Secondly, the situational awareness model is applied to the developed reliable routing process because picking the most reliable route does not guarantee reliable transmission. Therefore, a situation-aware reliable multipath routing algorithm for VANETs is proposed. Thirdly, the Ant Colony Optimisation (ACO) technique is employed to propose an Ant-based multi-constrained QoS (AMCQ) routing algorithm for VANETs. AMCQ is designed to give significant advantages to the implementation of security mechanisms that are intended to protect the QoS routing process. Finally, a novel set of security procedures is proposed to defend the routing process against external and internal threats. Simulation results demonstrate that high levels of QoS can be still guaranteed by AMCQ even when the security procedures are applied

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

Network-Based Management for Optimising Video Delivery

The past decade has witnessed a massive increase in Internet video traffic. The Cisco Visual Forecast index indicates that, by 2022, (79%) of the world's mobile data traffic will be video traffic. In order to increase the video streaming market revenue, service providers need to provide services to the end-users characterised by high Quality of Experience (QoE). However, delivering good-quality video services is a very challenging task due to the stringent constraints related to bandwidth and latency requirements in video streaming. Among the available streaming services, HTTP adaptive streaming (HAS) has become the de facto standard for multimedia delivery over the Internet. HAS is a pull-based approach, since the video player at the client side is responsible for adapting the requested video based on the estimated network conditions. Furthermore, HAS can traverse any firewall or proxy server that lets through standard HTTP data traffic over content delivery networks. Despite the great benefits HAS solutions bring, they also face challenges relating to quality fluctuations when they compete for a shared link. To overcome these issues, the network and video providers must exchange information and cooperate. In this context, Software Defined Networking (SDN) is an emerging technology used to deploy such architecture by providing centralised control for efficient and flexible network management. One of the first problems addressed in this thesis is that of providing QoE-level fairness for the competing HAS players and efficient resource allocation for the available network resources. This has been achieved by presenting a dynamic programming-based algorithm, based on the concept of Max-Min fairness, to provide QoE-level fairness among the competing HAS players. In order to deploy the proposed algorithm, an SDN-based architecture has been presented, named BBGDASH, that leverages the flexibility of the SDN’s management and control to deploy the proposed algorithm on the application and the network level. Another question answered by this thesis is that of how the proposed guidance approach maintains a balance between stability and scalability. To answer this question, a scalable guidance mechanism has been presented that provides guidance to the client without moving the entire control logic to an additional entity or relying purely on the client-side decision. To do so, the guidance scheme provides each client with the optimal bitrate levels to adapt the requested bitrate within the provided levels. Although the proposed BGGDASH can improve the QoE within a wired network, deploying it in a wireless network environment could result in sub-optimal decisions being made due to the high level of fluctuations in the wireless environment. In order to cope with this issue, two time series-based forecasting approaches have been presented to identify the optimal set of bitrate levels for each client based on the network conditions. Additionally, the implementation of the BBGDASH architecture has been extended by proposing an intelligent streaming architecture (named BBGDASH+). Finally, in order to evaluate the feasibility of deploying the bounding bitrate guidance with different network conditions, it has been evaluated under different network conditions to provide generic evaluations. The results show that the proposed algorithms can significantly improve the end-users QoE compared to other compared approaches