Analysis of Optimal Power-aware Scheduling Techniques in Embedded Systems for the Multiprocessor Platform Running Non-preemptive Jobs PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Analysis of Optimal Power-aware Scheduling Techniques in Embedded Systems for the Multiprocessor Platform Running Non-preemptive Jobs PDF full book. Access full book title Analysis of Optimal Power-aware Scheduling Techniques in Embedded Systems for the Multiprocessor Platform Running Non-preemptive Jobs by Rahul Ghosh. Download full books in PDF and EPUB format.
Author: Rahul Ghosh
Publisher:
ISBN:
Category : Computer scheduling
Languages : en
Pages : 192
Get Book Here
Book Description
Author: Rahul Ghosh
Publisher:
ISBN:
Category : Computer scheduling
Languages : en
Pages : 192
Get Book Here
Book Description
Author: Dawei Li
Publisher: Springer Science & Business Media
ISBN: 1461452236
Category : Business & Economics
Languages : en
Pages : 67
Get Book Here
Book Description
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.
Author: Sanjoy Baruah
Publisher: Springer
ISBN: 3319086960
Category : Technology & Engineering
Languages : en
Pages : 234
Get Book Here
Book Description
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.
Author: Muhammad Khurram Bhatti
Publisher: LAP Lambert Academic Publishing
ISBN: 9783846552056
Category :
Languages : en
Pages : 208
Get Book Here
Book Description
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.
Author: Jabran Khan Jadoon
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
The purpose of this study is to investigate how power management strategies can be efficiently exploited in actual platforms. Primarily, the challenges in multicore based embedded systems lies in managing the energy expenditure, determining the scheduling behavior and establishing methods to monitor power and energy, so as to meet the demands of the battery life and load requirements. The work presented in this dissertation is a study of low power-aware strategies in the practical world for single and multiprocessor platforms. The approach used for this study is based on representative multiprocessor platforms (real or virtual) to identify the most influential parameters, at hardware as well as application level, unlike many existing works in which these parameters are often underestimated or sometimes even ignored. The work analyzes and compares in detail various experimentations with different power policies based on Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Power Switching (DPS) techniques, and investigates the conditions at which these policies are effective in terms of energy savings. The results of these investigations reveal many interesting and notable conclusions that can serve as prerequisites for the efficient use of power management strategies. This work also shows the potential of advanced domain specific power strategies compared to real world available strategies that are general purpose based in their majority. Finally, some high level consumption models are derived from the different energy measurement results to let the estimation of power management benefits at early stages of a system development.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Power is a valuable resource in embedded systems as the lifetime of many such systems is constrained by their battery capacity. Recent advances in processor design have added support for dynamic frequency/voltage scaling (DVS) for saving power. Recent work on real-time scheduling focuses on saving power in static as well as dynamic scheduling environments by exploiting idle and slack due to early task completion for DVS of subsequent tasks. These scheduling algorithms rely on a priori knowledge of worst-case execution times (WCET) for each task. They assume that DVS has no effect on the worst-case execution cycles (WCEC) of a task and scale the WCET according to the processor frequency. However, for systems with memory hierarchies, the WCEC typically does change under DVS due to frequency modulation. Hence, current assumptions used by DVS schemes result in a highly exaggerated WCET. The research presented contributes novel techniques for tight and flexible static timing analysis particularly well-suited for dynamic scheduling schemes. The technical contributions are as follows: (1) The problem of changing execution cycles due to scaling techniques is assessed. (2) A parametric approach towards bounding the WCET statically with respect to the frequency is proposed. Using a parametric model, the effect of changes in frequency on the WCEC can be captured and, thus, the WCET over any frequency range can be accurately modeled. (3) The design and implementation of the frequency-aware static timing analysis (FAST) tool, based on prior experience with static timing analysis, is discussed. (4) Experiments demonstrate that the FAST tool provides safe upper bounds on the WCET, which are tight. The FAST tool allows the capture of the WCET of six benchmarks using equations that overestimate the WCET by less than 1%. FAST equations can also be used to improve existing DVS scheduling schemes to ensure that the effect of frequency scaling on WCET is considered and that the WCET use.
Author: Springer
Publisher:
ISBN: 9781461452256
Category :
Languages : en
Pages : 68
Get Book Here
Book Description
Author: Younès Chandarli
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
In this thesis, we are interested in the real-time fixed-priority scheduling problem of energy-harvesting systems. An energy-harvesting system is a system that can collect the energy from the environment in order to store it in a storage device and then to use it to supply an electronic device. This technology is used in small embedded systems that are required to run autonomously for a very long lifespan. Wireless sensor networks and medical implants are typical applications of this technology. Moreover, most of these devices have to execute many recurrent tasks within a limited time. Thus, these devices are subject to real-time constraints where the correctness of the system depends not only on the correctness of the results but also on the time in which they are delivered. This thesis focuses on the preemptive fixed-task-priority real-time scheduling for such systems in monoprocessor platforms. The problematic here is to find efficient scheduling algorithms and schedulability conditions that check the schedulability of a given task set in a given energy configuration. The first result of this thesis is the proposition of the PFPasap scheduling algorithm. It is an adaptation of the classical fixed-task-priority scheduling to the energy-harvesting context. It consists of executing tasks as soon as possible whenever the energy is sufficient to execute at least one time unit and replenishes otherwise. The replenishment periods are as long as needed to execute one time unit. We prove that PFPasap is optimal but only in the case of non-concrete systems where the first release time of tasks and the initial energy storage unit level are known only at run-time and where all the tasks consume more energy than the replenishment during execution times. A sufficient and necessary schedulability condition for such systems is also proposed. Unfortunately, when we relax the assumption of tasks energy consumption profile, by considering both tasks that consume more energy than the replenishment and the ones that consume less than the replenishment, PFPasap is no longer optimal and the worst-case scenario is no longer the synchronous release of all the tasks, which makes the precedent schedulability test only necessary. To cope with this limitation, we propose to upper bound tasks worst-case response time in order to build sufficient schedulability conditions instead of exact ones. Regarding algorithms optimality, we explore different ideas in order to build an optimal algorithm for the general model of fixed-task-priority tasks by considering all types of task sets and energy consumption profiles. We show through some counter examples the difficulty of finding such an algorithm and we show that most of intuitive scheduling algorithms are not optimal. After that, we discuss the possibility of finding such an algorithm. In order to better understand the scheduling problematic of fixed-priority scheduling for energy-harvesting systems, we also try to explore the solutions of similar scheduling problematics, especially the ones that delay executions in order to guarantee some requirements. The thermal-aware scheduling is one of these problematics. It consists of executing tasks such that a maximum temperature is never exceeded. This may lead to introduce additional idle times to cool down the system in order to prevent reaching the maximum temperature. As a first step, we propose in this thesis to adapt the solutions proposed for energy-harvesting systems to the thermal-aware model. Thus, we adapt the PFPasap algorithm to respect the thermal constraints and we propose a sufficient schedulability analysis based on worst-case response time upper bounds. Finally, we present YARTISS: the simulation tool used to evaluate the theoretical results presented in this dissertation.
Author:
Publisher:
ISBN:
Category : Operating systems (Computers)
Languages : en
Pages : 580
Get Book Here
Book Description
Author: Hessam Kooti
Publisher:
ISBN: 9781267646286
Category :
Languages : en
Pages : 168
Get Book Here
Book Description
In order to cope with increase in demand for embedded applications under resource and power constraints, there is an increasing trend on incorporating system-level flexibility and runtime adaptation in embedded systems. Although a complete processor-based implementation provides ultimate flexibility, usually computationally intensive processing mandates hardware support in addition to the processors. However, the main drawback of reconfigurable hardware platform is delay and energy overhead during system reconfiguration. Ignoring the time and energy required for reconfiguration may lead to performance degradation and deadline misses. In this thesis we provide different real-time scheduling techniques. First, we propose the first real-time scheduler that is aware of the transition time overhead due to configuration of underlying hardware. We consider a heterogeneous multi-processor system and there are data dependencies among tasks and communication overhead time during task execution. In many applications deadline miss rate is not an accurate metric to model the application quality but the distribution of deadline misses is the main factor. We use a well-known Weakly Hard System QoS model to define the acceptable deadline miss distribution. We provide an online scheduler that considers the time overheads among task switching while the deadline misses caused by time overheads follow a predefined pattern. Next, we focus on energy consumption of the system and provide a scheduler that considers the time and energy overhead during power management. In our work deadline miss rate is minimized as the primary objective and the energy consumption of the system is minimized by means of voltage scaling as the secondary objective. Many adaptive systems need to adapt to varying delay and/or energy constraints such as fluctuation of energy source when system is powered by renewable energies like solar energy. In order to ensure the scheduler can handle the dynamicity in availability of the energy source, we exploit the QoS constraint so the application quality is not violated during job dropout when our power management scheme adjusts the energy consumption according to energy availability. Each of these schedulers is accompanied by an extensive experimental evaluation that represents the effect of using the proposed algorithms.
