Abstract Data variety is one of the most important features Big Data. result aggregating data from multiple sources and uneven distribution data. This feature causes high variation in consumption processing resources such as CPU consumption. issue has been overlooked previous works. To overcome mentioned problem, present work, we used Dynamic Voltage Frequency Scaling (DVFS) to reduce energy co...

A process, voltage and temperature (PVT) sensors with dynamic voltage selection are proposed for environmental management in the ultra-low voltage dynamic voltage and frequency scaling (DVFS) system. The process and voltage (PV) sensors initially monitor the process variation. With known process information, PV sensors can real-time provide voltage variation status. The temperature sensor has s...

The management of energy consumption in battery-operated embedded and pervasive systems is increasingly important in order to extend battery lifetime or to increase the number of applications that can use the system’s resources. Dynamic voltage and frequency scaling (DVFS) has been introduced to trade off system performance with energy consumption. For real-time applications, systems supporting...

Portable, embedded systems place ever-increasing demands on high-performance, low-power microprocessor design. Dynamic voltage and frequency scaling (DVFS) is a wellknown technique to reduce energy in portable systems, but DVFS effectiveness suffers from the fact that voltage transitions occur on the order of tens of microseconds. Voltage regulators that are integrated on the same chip as the m...

Dynamic voltage and frequency scaling (DVFS) is a technique for adjusting the speed and power consumption of processors, allowing performance to be traded for reduced power consumption. Since CPUs are typically the largest consumers of power in modern servers, DVFS can have a significant impact on overall server power consumption. Modern operating systems include DVFS governors, which interact ...

Dynamic Voltage and Frequency Scaling (DVFS) schemes have shown to be effective in reducing the energy requirements of hand held devices such as smartphones. Current system-wide DVFS schemes act upon statistics of historical performance measures. As a result these schemes react after certain events have manifested. Being proactive to these events may yield more energy and performance gains. We ...

The Intel Single Chip Cloud Computer (SCC) architecture offers the adjustment of voltage and frequency on individual islands in a certain range and in a certain dependability to each other. This possibility offers a high degree of freedom for workload balancing which can be done statically (at compile time) or dynamically (at run-time). Especially the latter topic, the dynamic voltage and frequ...

Efficient task mapping plays a crucial role in saving energy in asymmetric multiprocessor platforms. This paper considers the problem of energy-aware static mapping of periodic realtime dependent tasks sharing resources on asymmetric multi/many-core embedded systems. The paper extends an existing synchronization-aware bin-packing (BP) variant when the full-chip dynamic voltage and frequency sca...

Abstract Dynamic voltage and frequency scaling (DVFS) is a promising broadly used energy-efficient technique to overcome the main problems arising from using finite energy reservoir capacity uncertain source in real-time embedded systems. This work investigates an management scheme for task scheduling variable processors located sensor nodes powered by ambient sources. We use DVFS decrease cons...

We report on our experience in implementing and evaluating nine, state-of-the-art single and multicore real-time dynamic voltage and frequency scaling (DVFS) schedulers on an embedded Linux platform. The algorithms include CC-EDF, LA-EDF, DRA, AGR, CVFS, and DR, among others, and the platform is a dual-core ARM Cortex-A9 MPCore processor/PandaBoard, running a real-time Linux kernel. Our evaluat...