Energy-Aware Scheduling for Streaming Applications

Streaming applications have become increasingly important and widespread,with application domains ranging from embedded devices to server systems.Traditionally, researchers have been focusing on improving the performanceof streaming applications to achieve high throughput and low response time.However, increasingly more attention is being shifted topower/performance trade-offbecause power consumption has become a limiting factor on system designas integrated circuits enter the realm of nanometer technology.This work addresses the problem of scheduling a streaming application(represented by a task graph)with the goal of minimizing its energy consumptionwhile satisfying its two quality of service (QoS) requirements,namely, throughput and response time.The available power management mechanisms are dynamic voltage scaling (DVS),which has been shown to be effective in reducing dynamic power consumption, andvary-on/vary-off, which turns processors on and off to save static power consumption.Scheduling algorithms are proposed for different computing platforms (uniprocessor and multiprocessor systems),different characteristics of workload (deterministic and stochastic workload),and different types of task graphs (singleton and general task graphs).Both continuous and discrete processor power models are considered.The highlights are a unified approach for obtaining optimal (or provably close to optimal)uniprocessor DVS schemes for various DVS strategies anda novel multiprocessor scheduling algorithm that exploits the differencebetween the two QoS requirements to perform processor allocation,task mapping, and task speedscheduling simultaneously

Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems

Over the past several decades, we have experienced tremendous growth of real-time systems in both scale and complexity. This progress is made possible largely due to advancements in semiconductor technology that have enabled the continuous scaling and massive integration of transistors on a single chip. In the meantime, however, the relentless transistor scaling and integration have dramatically increased the power consumption and degraded the system reliability substantially. Traditional real-time scheduling techniques with the sole emphasis on guaranteeing timing constraints have become insufficient. In this research, we studied the problem of how to develop advanced scheduling methods on hard real-time systems that are subject to multiple design constraints, in particular, timing, energy consumption, and reliability constraints. To this end, we first investigated the energy minimization problem with fault-tolerance requirements for dynamic-priority based hard real-time tasks on a single-core processor. Three scheduling algorithms have been developed to judiciously make tradeoffs between fault tolerance and energy reduction since both design objectives usually conflict with each other. We then shifted our research focus from single-core platforms to multi-core platforms as the latter are becoming mainstream. Specifically, we launched our research in fault-tolerant multi-core scheduling for fixed-priority tasks as fixed-priority scheduling is one of the most commonly used schemes in the industry today. For such systems, we developed several checkpointing-based partitioning strategies with the joint consideration of fault tolerance and energy minimization. At last, we exploited the implicit relations between real-time tasks in order to judiciously make partitioning decisions with the aim of improving system schedulability. According to the simulation results, our design strategies have been shown to be very promising for emerging systems and applications where timeliness, fault-tolerance, and energy reduction need to be simultaneously addressed

Network-on-Chip

Addresses the Challenges Associated with System-on-Chip Integration Network-on-Chip: The Next Generation of System-on-Chip Integration examines the current issues restricting chip-on-chip communication efficiency, and explores Network-on-chip (NoC), a promising alternative that equips designers with the capability to produce a scalable, reusable, and high-performance communication backbone by allowing for the integration of a large number of cores on a single system-on-chip (SoC). This book provides a basic overview of topics associated with NoC-based design: communication infrastructure design, communication methodology, evaluation framework, and mapping of applications onto NoC. It details the design and evaluation of different proposed NoC structures, low-power techniques, signal integrity and reliability issues, application mapping, testing, and future trends. Utilizing examples of chips that have been implemented in industry and academia, this text presents the full architectural design of components verified through implementation in industrial CAD tools. It describes NoC research and developments, incorporates theoretical proofs strengthening the analysis procedures, and includes algorithms used in NoC design and synthesis. In addition, it considers other upcoming NoC issues, such as low-power NoC design, signal integrity issues, NoC testing, reconfiguration, synthesis, and 3-D NoC design. This text comprises 12 chapters and covers: The evolution of NoC from SoC—its research and developmental challenges NoC protocols, elaborating flow control, available network topologies, routing mechanisms, fault tolerance, quality-of-service support, and the design of network interfaces The router design strategies followed in NoCs The evaluation mechanism of NoC architectures The application mapping strategies followed in NoCs Low-power design techniques specifically followed in NoCs The signal integrity and reliability issues of NoC The details of NoC testing strategies reported so far The problem of synthesizing application-specific NoCs Reconfigurable NoC design issues Direction of future research and development in the field of NoC Network-on-Chip: The Next Generation of System-on-Chip Integration covers the basic topics, technology, and future trends relevant to NoC-based design, and can be used by engineers, students, and researchers and other industry professionals interested in computer architecture, embedded systems, and parallel/distributed systems

Energy management in content distribution network servers

Les infrastructures Internet et l'installation d'appareils très gourmands en énergie (en raison de l'explosion du nombre d'internautes et de la concurrence entre les services efficaces offerts par Internet) se développent de manière exponentielle. Cela entraîne une augmentation importante de la consommation d'énergie. La gestion de l'énergie dans les systèmes de distribution de contenus à grande échelle joue un rôle déterminant dans la diminution de l'empreinte énergétique globale de l'industrie des TIC (Technologies de l'information et de la communication). Elle permet également de diminuer les coûts énergétiques d'un produit ou d'un service. Les CDN (Content Delivery Networks) sont parmi les systèmes de distribution à grande échelle les plus populaires, dans lesquels les requêtes des clients sont transférées vers des serveurs et traitées par des serveurs proxy ou le serveur d'origine, selon la disponibilité des contenus et la politique de redirection des CDN. Par conséquent, notre objectif principal est de proposer et de développer des mécanismes basés sur la simulation afin de concevoir des politiques de redirection des CDN. Ces politiques prendront la décision dynamique de réduire la consommation d'énergie des CDN. Enfin, nous analyserons son impact sur l'expérience utilisateur. Nous commencerons par une modélisation de l'utilisation des serveurs proxy et un modèle de consommation d'énergie des serveurs proxy basé sur leur utilisation. Nous ciblerons les politiques de redirection des CDN en proposant et en développant des politiques d'équilibre et de déséquilibre des charges (en utilisant la loi de Zipf) pour rediriger les requêtes des clients vers les serveurs. Nous avons pris en compte deux techniques de réduction de la consommation d'énergie : le DVFS (Dynamic Voltage Frequency Scaling) et la consolidation de serveurs. Nous avons appliqué ces techniques de réduction de la consommation d'énergie au contexte d'un CDN (au niveau d'un serveur proxy), mais aussi aux politiques d'équilibre et de déséquilibre des charges afin d'économiser l'énergie. Afin d'évaluer les politiques et les mécanismes que nous proposons, nous avons mis l'accent sur la manière de rendre l'utilisation des ressources des CDN plus efficace, mais nous nous sommes également intéressés à leur coût en énergie, à leur impact sur l'expérience utilisateur et sur la qualité de la gestion des infrastructures. Dans ce but, nous avons défini comme métriques d'évaluation l'utilisation des serveurs proxy, d'échec des requêtes comme les paramètres les plus importants. Nous avons transformé un simulateur d'événements discrets CDNsim en Green CDNsim, et évalué notre travail selon différents scénarios de CDN en modifiant : les infrastructures proxy des CDN (nombre de serveurs proxy), le trafic (nombre de requêtes clients) et l'intensité du trafic (fréquence des requêtes client) en prenant d'abord en compte les métriques d'évaluation mentionnées précédemment. Nous sommes les premiers à proposer un DVFS et la combinaison d'un DVFS avec la consolidation d'un environnement de simulation de CDN en prenant en compte les politiques d'équilibre et de déséquilibre des charges. Nous avons conclu que les techniques d'économie d'énergie permettent de réduire considérablement la consommation d'énergie mais dégradent l'expérience utilisateur. Nous avons montré que la technique de consolidation des serveurs est plus efficace dans la réduction d'énergie lorsque les serveurs proxy ne sont pas beaucoup chargés. Dans le même temps, il apparaît que l'impact du DVFS sur l'économie d'énergie est plus important lorsque les serveurs proxy sont bien chargés. La combinaison des deux (DVFS et consolidation des serveurs) permet de consommer moins d'énergie mais dégrade davantage l'expérience utilisateur que lorsque ces deux techniques sont utilisées séparément.Explosive increase in Internet infrastructure and installation of energy hungry devices because of huge increase in Internet users and competition of efficient Internet services causing a great increase in energy consumption. Energy management in large scale distributed systems has an important role to minimize the contribution of Information and Communication Technology (ICT) industry in global CO2 (Carbon Dioxide) footprint and to decrease the energy cost of a product or service. Content distribution Networks (CDNs) are one of the popular large scale distributed systems, in which client requests are forwarded towards servers and are fulfilled either by surrogate servers or by origin server, depending on contents availability and CDN redirection policy. Our main goal is therefore, to propose and to develop simulation-based principled mechanisms for the design of CDN redirection policies which will do and carry out dynamic decisions to reduce CDN energy consumption and then to analyze its impact on user experience constraints to provide services. We started from modeling surrogate server utilization and derived surrogate server energy consumption model based on its utilization. We targeted CDN redirection policies by proposing and developing load-balance and load-unbalance policies using Zipfian distribution, to redirect client requests to servers. We took into account two energy reduction techniques, Dynamic Voltage Frequency Scaling (DVFS) and server consolidation. We applied these energy reduction techniques in the context of a CDN at surrogate server level and injected them in load-balance and load-unbalance policies to have energy savings. In order to evaluate our proposed policies and mechanisms, we have emphasized, how efficiently the CDN resources are utilized, at what energy cost, its impact on user experience and on quality of infrastructure management. For that purpose, we have considered surrogate server's utilization, energy consumption, energy per request, mean response time, hit ratio and failed requests as evaluation metrics. In order to analyze energy reduction and its impact on user experience, energy consumption, mean response time and failed requests are considered more important parameters. We have transformed a discrete event simulator CDNsim into Green CDNsim and evaluated our proposed work in different scenarios of a CDN by changing: CDN surrogate infrastructure (number of surrogate servers), traffic load (number of client requests) and traffic intensity (client requests frequency) by taking into account previously discussed evaluation metrics. We are the first who proposed DVFS and the combination of DVFS and consolidation in a CDN simulation environment, considering load-balance and loadunbalance policies. We have concluded that energy reduction techniques offer considerable energy savings while user experience is degraded. We have exhibited that server consolidation technique performs better in energy reduction while surrogate servers are lightly loaded. While, DVFS impact is more considerable for energy gains when surrogate servers are well loaded. Impact of DVFS on user experience is lesser than that of server consolidation. Combination of both (DVFS and server consolidation) presents more energy savings at higher cost of user experience degradation in comparison when both are used individually

A unified approach to variable voltage scheduling for nonideal DVS processors

Abstract—Voltage scheduling is an essential technique used to exploit the benefit of dynamic voltage-scaling processors.Though extensive research exists in this area, current processor limitations such as time and energy transition overhead and voltage-level discretization are often dismissed as insignificant.We show that for hard real-time applications, disregarding these details can lead to suboptimal or even invalid results.We propose two algorithms to account for these limitations.The first is a greedy approach, while the second is more complex, but can significantly reduce the system’s energy consumption.Through experimental results on both real and randomly generated systems, we show the effectiveness of both algorithms and explore what conditions make it beneficial to use the complex algorithm over the basic one. Index Terms—Embedded systems, low-power design, power minimization, scheduling, simulation. I