Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth. This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics. To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.

Nowadays, computer systems are everywhere. From simple portable devices such as watches and MP3 players to large stationary installations that control nuclear power plants, computer systems are now present in all aspects of our modern and every-day life. In about only 70 years, they have completely perturbed our way of life and they reached a so high degree of sophistication that they will be soon capable of driving our cars and cleaning our houses without any human intervention. As computer systems gain in responsibilities, it becomes essential that they provide both safety and reliability. Indeed, a failure in systems such as the anti-lock braking system (ABS) in cars could threaten human lives and generate catastrophic and irreversible consequences. Hence, for many years, researchers have addressed these emerging problems of system safety and reliability which come along with this fulgurant evolution. This thesis provides a general overview of embedded real-time computer systems, i.e., a particular kind of computer system whose number grows daily. We provide the reader with some preliminary knowledge and a good understanding of the concepts that underlie this emerging technology. We focus especially on the theoretical problems related to the real-time issue and briefly summarizes the main solutions, together with their advantages and drawbacks. This brings the reader through all the conceptual layers constituting a computer system, from the software level---the logical part---that specifies both the system behavior and requirements to the hardware level---the physical part---that actually performs the expected treatments and reacts to the environment. In the meanwhile, we introduce the theoretical models that allow researchers for theoretical analyses which ensure that all the system requirements are fulfilled. Finally, we address the energy consumption problem in embedded systems. We describe the various factors of power dissipation in modern technologies and we introduce different solutions to reduce this consumption./Cette thèse se focalise sur un type de systèmes informatiques bien précis appelés “systèmes embarqués temps réel”. Un système est dit “embarqué” lorsqu’il est développé afin de servir un but bien précis. Un téléphone portable est un parfait exemple de système embarqué étant donné que toutes ses fonctionnalités sont rigoureusement définies avant même sa conception. Au contraire, un ordinateur personnel n’est généralement pas considéré comme un système embarqué, les concepteurs ne sachant pas à l’avance à quelles fins il sera utilisé. Une grande partie de ces systèmes embarqués ont des contraintes temporelles très fortes, ce qui les distingue encore plus des ordinateurs grand public. A titre d’exemple, lorsqu’un conducteur de voiture freine brusquement, l’ordinateur de bord déclenche l’application ABS et il est primordial que cette application soit traitée endéans une courte échéance. Autrement dit, cette fonctionnalité ABS doit être traitée prioritairement par rapport aux autres fonctionnalités du véhicule. Ce type de système embarqué est alors dit “temps réel”, dû à ces notions de temps et de priorités entre les applications. La problèmatique posée par les systèmes temps réel est la suivante. Comment déterminer, à tout moment, un ordre d’exécution des différentes fonctionnalités de telle sorte qu’elles soient toutes exécutées entièrement endéans leur échéance ? De plus, avec l’apparition récente des systèmes multiprocesseurs, cette problématique s’est fortement complexifiée, vu que le système doit à présent déterminer quelle fonctionnalité s’exécute à quel moment sur quel processeur afin que toutes les contraintes temporelles soient respectées. Pour finir, ces systèmes embarqués temp réel multiprocesseurs se sont rapidement retrouvés confrontés à un problème de consommation d’énergie. Leur demande en terme de performance (et donc en terme d’énergie) à évolué beaucoup plus rapidement que la capacité des batteries qui les alimentent. Ce problème est actuellement rencontré par de nombreux systèmes, tels que les téléphones portables par exemple. L’objectif de cette thèse est de parcourir les différents composants de tels système embarqués et de proposer des solutions afin de réduire leur consommation d’énergie.

Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth. This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics. To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.

Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth. This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics. To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.

Only if humanity acts quickly and resolutely can we limit global warming' conclude more than 25,000 academics with the statement of SCIENTISTS FOR FUTURE. The concern about global warming and the extinction of species has steadily increased in recent years.

Nowadays, computer systems are everywhere. From simple portable devices such as watches and MP3 players to large stationary installations that control nuclear power plants, computer systems are now present in all aspects of our modern and every-day life. In about only 70 years, they have completely perturbed our way of life and they reached a so high degree of sophistication that they will be soon capable of driving our cars and cleaning our houses without any human intervention. As computer systems gain in responsibilities, it becomes essential that they provide both safety and reliability. Indeed, a failure in systems such as the anti-lock braking system (ABS) in cars could threaten human lives and generate catastrophic and irreversible consequences. Hence, for many years, researchers have addressed these emerging problems of system safety and reliability which come along with this fulgurant evolution. <p><p>This thesis provides a general overview of embedded real-time computer systems, i.e. a particular kind of computer system whose number grows daily. We provide the reader with some preliminary knowledge and a good understanding of the concepts that underlie this emerging technology. We focus especially on the theoretical problems related to the real-time issue and briefly summarizes the main solutions, together with their advantages and drawbacks. This brings the reader through all the conceptual layers constituting a computer system, from the software level---the logical part---that specifies both the system behavior and requirements to the hardware level---the physical part---that actually performs the expected treatments and reacts to the environment. In the meanwhile, we introduce the theoretical models that allow researchers for theoretical analyses which ensure that all the system requirements are fulfilled. Finally, we address the energy consumption problem in embedded systems. We describe the various factors of power dissipation in modern technologies and we introduce different solutions to reduce this consumption./Cette thèse se focalise sur un type de systèmes informatiques bien précis appelés “systèmes embarqués temps réel”. Un système est dit “embarqué” lorsqu’il est développé afin de servir un but bien précis. Un téléphone portable est un parfait exemple de système embarqué étant donné que toutes ses fonctionnalités sont rigoureusement définies avant même sa conception. Au contraire, un ordinateur personnel n’est généralement pas considéré comme un système embarqué, les concepteurs ne sachant pas à l’avance à quelles fins il sera utilisé. Une grande partie de ces systèmes embarqués ont des contraintes temporelles très fortes, ce qui les distingue encore plus des ordinateurs grand public. A titre d’exemple, lorsqu’un conducteur de voiture freine brusquement, l’ordinateur de bord déclenche l’application ABS et il est primordial que cette application soit traitée endéans une courte échéance. Autrement dit, cette fonctionnalité ABS doit être traitée prioritairement par rapport aux autres fonctionnalités du véhicule. Ce type de système embarqué est alors dit “temps réel”, dû à ces notions de temps et de priorités entre les applications. La problèmatique posée par les systèmes temps réel est la suivante. Comment déterminer, à tout moment, un ordre d’exécution des différentes fonctionnalités de telle sorte qu’elles soient toutes exécutées entièrement endéans leur échéance ?De plus, avec l’apparition récente des systèmes multiprocesseurs, cette problématique s’est fortement complexifiée, vu que le système doit à présent déterminer quelle fonctionnalité s’exécute à quel moment sur quel processeur afin que toutes les contraintes temporelles soient respectées. Pour finir, ces systèmes embarqués temp réel multiprocesseurs se sont rapidement retrouvés confrontés à un problème de consommation d’énergie. Leur demande en terme de performance (et donc en terme d’énergie) à évolué beaucoup plus rapidement que la capacité des batteries qui les alimentent. Ce problème est actuellement rencontré par de nombreux systèmes, tels que les téléphones portables par exemple. L’objectif de cette thèse est de parcourir les différents composants de tels système embarqués et de proposer des solutions afin de réduire leur consommation d’énergie. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished