DyPS: Dynamic Processor Switching for Energy-Aware Video Decoding on Multi-core SoCs

In addition to General Purpose Processors (GPP), Multicore SoCs equipping modern mobile devices contain specialized Digital Signal Processor designed with the aim to provide better performance and low energy consumption properties. However, the experimental measurements we have achieved revealed that system overhead, in case of DSP video decoding, causes drastic performances drop and energy efficiency as compared to the GPP decoding. This paper describes DyPS, a new approach for energy-aware processor switching (GPP or DSP) according to the video quality . We show the pertinence of our solution in the context of adaptive video decoding and describe an implementation on an embedded Linux operating system with the help of the GStreamer framework. A simple case study showed that DyPS achieves 30% energy saving while sustaining the decoding performanc

Band Codes for Energy-Efficient Network Coding with Application to P2P Mobile Streaming

A key problem in random network coding (NC) lies in the complexity and energy consumption associated with the packet decoding processes, which hinder its application in mobile environments. Controlling and hence limiting such factors has always been an important but elusive research goal, since the packet degree distribution, which is the main factor driving the complexity, is altered in a non-deterministic way by the random recombinations at the network nodes. In this paper we tackle this problem proposing Band Codes (BC), a novel class of network codes specifically designed to preserve the packet degree distribution during packet encoding, ecombination and decoding. BC are random codes over GF(2) that exhibit low decoding complexity, feature limited and controlled degree distribution by construction, and hence allow to effectively apply NC even in energy-constrained scenarios. In particular, in this paper we motivate and describe our new design and provide a thorough analysis of its performance. We provide numerical simulations of the performance of BC in order to validate the analysis and assess the overhead of BC with respect to a onventional NC scheme. Moreover, peer-to-peer media streaming experiments with a random-push protocol show that BC reduce the decoding complexity by a factor of two, to a point where NC-based mobile streaming to mobile devices becomes practically feasible.Comment: To be published in IEEE Transacions on Multimedi

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

Sweet Streams are Made of This: The System Engineer's View on Energy Efficiency in Video Communications

In recent years, the global use of online video services has increased rapidly. Today, a manifold of applications, such as video streaming, video conferencing, live broadcasting, and social networks, make use of this technology. A recent study found that the development and the success of these services had as a consequence that, nowadays, more than 1% of the global greenhouse-gas emissions are related to online video, with growth rates close to 10% per year. This article reviews the latest findings concerning energy consumption of online video from the system engineer's perspective, where the system engineer is the designer and operator of a typical online video service. We discuss all relevant energy sinks, highlight dependencies with quality-of-service variables as well as video properties, review energy consumption models for different devices from the literature, and aggregate these existing models into a global model for the overall energy consumption of a generic online video service. Analyzing this model and its implications, we find that end-user devices and video encoding have the largest potential for energy savings. Finally, we provide an overview of recent advances in energy efficiency improvement for video streaming and propose future research directions for energy-efficient video streaming services.Comment: 16 pages, 5 figures, accepted for IEEE Circuits and Systems Magazin

QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

The Chameleon Architecture for Streaming DSP Applications

We focus on architectures for streaming DSP applications such as wireless baseband processing and image processing. We aim at a single generic architecture that is capable of dealing with different DSP applications. This architecture has to be energy efficient and fault tolerant. We introduce a heterogeneous tiled architecture and present the details of a domain-specific reconfigurable tile processor called Montium. This reconfigurable processor has a small footprint (1.8 mm$^2$ in a 130 nm process), is power efficient and exploits the locality of reference principle. Reconfiguring the device is very fast, for example, loading the coefficients for a 200 tap FIR filter is done within 80 clock cycles. The tiles on the tiled architecture are connected to a Network-on-Chip (NoC) via a network interface (NI). Two NoCs have been developed: a packet-switched and a circuit-switched version. Both provide two types of services: guaranteed throughput (GT) and best effort (BE). For both NoCs estimates of power consumption are presented. The NI synchronizes data transfers, configures and starts/stops the tile processor. For dynamically mapping applications onto the tiled architecture, we introduce a run-time mapping tool

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

A pixel-based complexity model to estimate energy consumption in video decoders

The increasing use of HEVC video streams in diverse multimedia applications is driving the need for higher user control and management of energy consumption in battery-powered devices. This paper presents a contribution for the lack of adequate solutions by proposing a pixel-based complexity model that is capable of estimating the energy consumption of an arbitrary software-based HEVC decoder, running on different hardware platforms and devices. In the proposed model, the computational complexity is defined as a linear function of the number of pixels processed by the main decoding functions, using weighting coefficients which represent the average computational effort that each decoding function requires per pixel. The results shows that the cross-correlation of frame-based complexity estimation with energy consumption is greater than 0.86. The energy consumption of video decoding is estimated with the proposed model within an average deviation range of about 6.9%, for different test sequences.info:eu-repo/semantics/publishedVersio