Energy Aware Scheduling On Multiprocessor Platforms

Multiprocessor platforms play important roles in modern computing systems, and appear in various applications, ranging from energy-limited hand-held devices to large data centers. As the performance requirements increase, energy-consumption in these systems also increases significantly. Dynamic Voltage and Frequency Scaling (DVFS), which allows processors to dynamically adjust the supply voltage and the clock frequency to operate on different power/energy levels, is considered an effective way to achieve the goal of energy-saving. This book surveys existing works that have been on energy-aware task scheduling on DVFS multiprocessor platforms. Energy-aware scheduling problems are intrinsically optimization problems, the formulations of which greatly depend on the platform and task models under consideration. Thus, Energy-aware Scheduling on Multiprocessor Platforms covers current research on this topic and classifies existing works according to two key standards, namely, homogeneity/heterogeneity of multiprocessor platforms and the task types considered. Under this classification, other sub-issues are also included, such as, slack reclamation, fixed/dynamic priority scheduling, partition-based/global scheduling, and application-specific power consumption, etc.

Real-time embedded systems have become ubiquitous in our daily life. Due to their diversified usage, the research on these systems has confronted with many emerging challenges. One such challenge is to reduce power and energy consumption while maintaining assurance that timing constraints will be met. Power densities in microprocessors are almost doubled every three years. As energy is power integrated over time, supplying the required energy may become prohibitively expensive, or even technologically infeasible. This is particularly difficult in portable systems that heavily rely on batteries for energy, and will become even more critical as battery capacities are increasing at a much slower rate than power consumption. This book presents four contributions that are based on the thesis that energy-efficiency of Real-time Embedded Systems and scheduling are closely related problems and therefore, should be tackled together for optimal results. Contributions of this book are: 1) Two-level Hierarchical Scheduling Algorithm for Multiprocessor Systems, 2) Assertive Dynamic Power Management Scheme, 3) Deterministic Stretch-to-Fit DVFS Technique, and 4) Hybrid Power Management Scheme.

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront

Increasing size and complexity of software and hardware systems makes it harder to ensure their reliability. At the same time, the issues of autonomous computing become more critical as we more and more rely on software systems in our daily life. Such complexity is getting even more critical with the ubiquitous computing of embedded devices and other pervasive systems. These trends ask for techniques and tools for developing reliable and autonomous software which can support software engineers in their efforts. This book summarizes the state of the art of research in the diverse fields concerned, including novel designs, case studies and experimental as well as theoretical results.

To the hard-pressed systems designer this book will come as a godsend. It is a hands-on guide to the many ways in which processor-based systems are designed to allow low power devices. Covering a huge range of topics, and co-authored by some of the field’s top practitioners, the book provides a good starting point for engineers in the area, and to research students embarking upon work on embedded systems and architectures.

Les applications temps réel modernes deviennent plus exigeantes en termes de ressources et de débit amenant la conception d’architectures multiprocesseurs. Ces systèmes, des équipements embarqués au calculateur haute performance, sont, pour des raisons d’autonomie et de fiabilité, confrontés à des problèmes cruciaux de consommation d’énergie. Pour ces raisons, cette thèse propose de nouvelles techniques d’optimisation de la consommation d’énergie dans l’ordonnancement de systèmes multiprocesseur. La première contribution est un algorithme d’ordonnancement hiérarchique à deux niveaux qui autorise la migration restreinte des tâches. Cet algorithme vise à réduire la sous-optimalité de l’algorithme global EDF. La deuxième contribution de cette thèse est une technique de gestion dynamique de la consommation nommée Assertive Dynamic Power Management (AsDPM). Cette technique, qui régit le contrôle d’admission des tâches, vise à exploiter de manière optimale les modes repos des processeurs dans le but de réduire le nombre de processeurs actifs. La troisième contribution propose une nouvelle technique, nommée Deterministic Strech-to-Fit (DSF), permettant d’exploiter le DVFS des processeurs. Les gains énergétiques observés s’approchent des solutions déjà existantes tout en offrant une complexité plus réduite. Ces techniques ont une efficacité variable selon les applications, amenant à définir une approche plus générique de gestion de la consommation appelée Hybrid Power Management (HyPowMan). Cette approche sélectionne, en cours d’exécution, la technique qui répond le mieux aux exigences énergie / performance.

This book constitutes the refereed proceedings of the 8th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2014, held in Belfast, UK, in December 2014. The 57 papers presented together with 7 papers of the workshop AmIUA 2014, 8 papers of the workshop IoT 2014, 7 papers of the workshop EUSPAI 2014, and 6 papers of the workshop VSS 2014 were carefully reviewed and selected from numerous submissions. The papers are grouped in topical sections on key application domains for ambient intelligence, human interaction in ambient intelligence, ICT instrumentation and middleware support for smart environments and objects, adding intelligence for environment adaption, and security and privacy issues in AAL.

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems. The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models. New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis. Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.