A case study of a system-level approach to power-aware computing (original) (raw)
Related papers
A Framework for Optimization of Power Consumption in Mobile Computing Devices
Mehran University Research Journal of Engineering and Technology, 2020
Battery driven computing devices such as laptops and cellular phones have become a necessity in this era. Mobile applications help us in daily life activities and with the rise of Internet of Things (IoT) new opportunities are open up to automate different task. However, batteries have their own limitations such as weight, cost, and size. Multiple applications and background processes running in parallel easily drain phone’s battery within 24 hours consequently annoying users by limited battery capacity. Repeated charge, recharge cycles steadily diminish the full capacity of batteries resulting in the immense decreased performance of the device. Therefore, mobile devices and mobile applications are in great need of energy-aware modules. In this paper, a survey is performed to identify the needs of the mobile user in the context of energy consumption problem. The results of survey lead authors to propose a middle layer energy aware framework to address this issue. The proposed framew...
Power conservation strategy for mobile computers using load sharing
ACM SIGMOBILE Mobile Computing and Communications Review, 1998
Power management is an important aspect of mobile computing. Previous works on power conservation have concentrated on the hardware approach. In this paper, we propose a different approach of power conservation strategy for mobile computers which is based on the concept of load sharing. User jobs are transferred from a mobile host to a fixed host to reduce power consumption by the CPU. Simulation results show that under suitable conditions, transferring job can extend battery lifetime by up to 20%. Transferring jobs to a fixed host does not only extend battery lifetime but also gives users access to faster machines, hence improving job response time.
A System-Level Model for Runtime Power Estimation on Mobile Devices
2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing, 2010
The growing popularity of mobile internet services, characterized by heavy network transmission, intensive computation and an always-on display, poses a great challenge to the battery lifetime of mobile devices. To manage the power consumption in an efficient way, it is essential to understand how the power is consumed at the system level and to be able to estimate the power consumption during runtime. Although the power modeling of each hardware component has been studied separately, there is no general solution at present of combining them into a system-level power model. In this paper we present a methodology for building a system-level power model without power measurement at the component level. We develop a linear regression model with nonnegative coefficients, which describes the aggregate power consumption of the processors, the wireless network interface and the display. Based on statistics and expert knowledge, we select three hardware performance counters, three network transmission parameters and one display parameter as regression variables. The power estimation, based on our model, exhibits 2.62% median error on real mobile internet services.
International Journal of Computer Applications, 2014
Power-aware computing has caught the interest of researchers and users of all computing systems. In embedded systems and small devices, better management of energy translates into longer lasting and smaller batteries, which in turn implies smaller and lighter devices. In cloud, distributed, and high performance computing systems, better management of power translates into saving a significant amount of money and natural resources. This paper surveys the different poweraware computing approaches and techniques, focusing mostly on software approaches. It also introduces power-aware computing and why it is very important these days. The paper discusses the ways and challenges of measuring the energy consumption of systems and devices.
The power broker: Intelligent power management for mobile computers
1996
∗University of Pennsylvania University of Pennsylvania, jms@cis.upenn.edu This paper is posted at ScholarlyCommons. http://repository.upenn.edu/cis reports/191 ... University of Pennsylvania School of Engineering and Applied Science Computer and Information Science Department
Controlling Energy Demand in Mobile Computing Systems
Synthesis Lectures on Mobile and Pervasive Computing, 2007
Mobile computing and pervasive computing represent major evolutionary steps in distributed systems, a line of research and development that dates back to the mid-1970s. Although many basic principles of distributed system design continue to apply, four key constraints of mobility have forced the development of specialized techniques. These include: unpredictable variation in network quality, lowered trust and robustness of mobile elements, limitations on local resources imposed by weight and size constraints, and concern for battery power consumption. Beyond mobile computing lies pervasive (or ubiquitous) computing, whose essence is the creation of environments saturated with computing and communication, yet gracefully integrated with human users. A rich collection of topics lies at the intersections of mobile and pervasive computing with many other areas of computer science.
International Journal of Embedded Systems, 2007
This paper summarizes the objectives and structure of a seminar with the same title, held from January 21st to January 26th at Schloss Dagstuhl, Germany. The seminar started from the results of the preceding Dagstuhl seminar 05141 on the same topic, and tried to identify emerging trends in three areas-low-power design and reliability, , and power estimation and simulation. The outcome of these discussions is also contained in this article.
Managing Shared Resources in Power Aware Systems
Mobile and portable computing devices based on microprocessors, cellular phones, portable digital agendas (PDA), etc. represent today an important part in the consumer electronic market. The commercial success of these products greatly depends on the duration of the battery support. In order to consume minimal energy during power-up, sleep, idle and underloaded conditions, many Dynamic Voltage Scaling (DVS) techniques have been proposed. In this paper, we propose a technique based on the resource reservation paradigm. The paradigm is extended to cope with shared resources and critical sections. The bandwidth reserved to each task is controlled by means of a predictor and a feedback algorithm. Taking into account the total utilization factor demand for the processor the frequency and voltage are scaled to keep the overall bandwidth close to 100%.
Characterizing system level energy consumption in mobile computing platforms
2005 International Conference on Wireless Networks, Communications and Mobile Computing, 2005
This paper approaches energy consumption characterization in mobile computing platforms by assessing energy consumption of "basic" application-level tasks, such as as processing, input/output (disk, display, etc.), communication (transmission and reception over the network), and combinations thereof. Besides providing information on the energy consumption behavior of typical tasks performed by mobile computers, task-level energy characterization enables power management decisions, such as whether, in a distributed computation, the task at hand can be executed locally or should be assigned to a different machine (given the machine's current energy budget, the energy cost of executing the task locally, and the cost of sending the required information over the network to a peer). We employ a task-level energy consumption characterization benchmark that accounts for basic tasks such as processing, disk access (including reads and writes), terminal usage, and communication (transmission and reception). Using the benchmark, we perform an energy characterization case study using the Dell Latitude C600 running two versions of the Linux operating system.