Fine-Grained Energy Consumption Characterization and Modeling

2010 ◽  
Author(s):  
Catherine Mills Olschanowsky ◽  
Tajana Rosing ◽  
Allan Snavely ◽  
Laura Carrington ◽  
Mustafa M. Tikir ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fine Grained

scholarly journals Worst-case energy consumption minimization based on interference analysis and bank mapping in multicore systems

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771668696
Author(s):  
Zhihua Gan ◽  
Zhimin Gu ◽  
Hai Tan ◽  
Mingquan Zhang ◽  
Jizan Zhang
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Multicore Systems ◽  
Worst Case ◽  
Mapping Algorithm ◽  
Fine Grained ◽  
Energy Consumption Reduction ◽  
Deadline Constraints ◽  
Core Mapping ◽  
The Impact

Energy is a scarce resource in real-time embedded systems due to the fact that most of them run on batteries. Hence, the designers should ensure that the energy constraints are satisfied in addition to the deadline constraints. This necessitates the consideration of the impact of the interference due to shared, low-level hardware resources such as the cache on the worst-case energy consumption of the tasks. Toward this aim, this article proposes a fine-grained approach to analyze the bank-level interference (bank conflict and bus access interference) on real-time multicore systems, which can reasonably estimate runtime interferences in shared cache and yield tighter worst-case energy consumption. In addition, we develop a bank-to-core mapping algorithm for reducing bank-level interference and improving the worst-case energy consumption. The experimental results demonstrate that our approach can improve the tightness of worst-case energy consumption by 14.25% on average compared to upper-bound delay approach. The bank-to-core mapping provides significant benefits in worst-case energy consumption reduction with 7.23%.

scholarly journals Adaptive Resource Allocation and Provisioning in Multi-Service Cloud Environments

2019 ◽  
pp. 372-381
Author(s):  
Anitha Nithya R ◽  
Saran A ◽  
Vinoth R
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Energy Aware ◽  
Research Issues ◽  
Allocation Policy ◽  
Fine Grained ◽  
Policy Problem ◽  
Machine Allocation

Minimizing the energy consumption and resource usage in cloud computing environment is one of the key research issues. Energy aware resource allocation is used to optimize the power consuming by computer resources and storage in cloud. The proposed system is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. Using migration for minimizing the number of active physical nodes the dynamic single threshold VM consolidation leverages fine-grained fluctuations in the workloads and continuously reallocates VMs . A genetic algorithm based power-aware scheduling of resource allocation (G-PARS) has been proposed to solve the dynamic virtual machine allocation policy problem. The experiment results show that strategy that has been proposed has a better performance than other strategies, not only in high Quality Of Service(QoS) but also in less energy consumption.

Privacy Preservation in Smart Grid Environment

2019 ◽  
pp. 158-182
Author(s):  
Muhammad Aminu Lawal ◽  
Syed Raheel Hassan
Keyword(s):  
Energy Consumption ◽  
Comparative Analysis ◽  
Smart Grid ◽  
Smart Grids ◽  
Privacy Preservation ◽  
User Privacy ◽  
Privacy And Security ◽  
Electricity Grid ◽  
Fine Grained ◽  
Comparison Table

Smart grids are conceived to ensure smarter generation, transmission, distribution, and consumption of electricity. It integrates the traditional electricity grid with information and communication technology. This enables a two-way communication among the smart grid entities, which translates to exchange of information about fine-grained user energy consumption between the smart grid entities. However, the flow of user energy consumption data may lead to the violation of user privacy. Inference on such data can expose the daily habits and types of appliances of users. Thus, several privacy preservation schemes have been proposed in the literature to ensure the privacy and security requirements of smart grid users. This chapter provides a review of some privacy preservation schemes. The schemes operational procedure, strengths, and weaknesses are discussed. A taxonomy, comparison table, and comparative analysis are also presented. The comparative analysis gives an insight on open research issues in privacy preservation schemes.

scholarly journals Fine-grained RNN with Transfer Learning for Energy Consumption Estimation on EVs

2022 ◽  
pp. 1-1
Author(s):  
Yining Hua ◽  
Michele Sevegnani ◽  
Dewei Yi ◽  
Andrew Birnie ◽  
Steve Mcaslan
Keyword(s):  
Energy Consumption ◽  
Transfer Learning ◽  
Fine Grained

scholarly journals A Novel Task Caching and Migration Strategy in Multi-Access Edge Computing Based on the Genetic Algorithm

2019 ◽  
Vol 11 (8) ◽  
pp. 181 ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Linyao Kang ◽  
Li Zhang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Mobile Devices ◽  
Minimum Energy ◽  
Edge Computing ◽  
Task Migration ◽  
Migration Strategy ◽  
Caching Strategy ◽  
Fine Grained ◽  
Multi Access

Multi-access edge computing (MEC) brings high-bandwidth and low-latency access to applications distributed at the edge of the network. Data transmission and exchange become faster, and the overhead of the task migration between mobile devices and edge cloud becomes smaller. In this paper, we adopt the fine-grained task migration model. At the same time, in order to further reduce the delay and energy consumption of task execution, the concept of the task cache is proposed, which involves caching the completed tasks and related data on the edge cloud. Then, we consider the limitations of the edge cloud cache capacity to study the task caching strategy and fine-grained task migration strategy on the edge cloud using the genetic algorithm (GA). Thus, we obtained the optimal mobile device task migration strategy, satisfying minimum energy consumption and the optimal cache on the edge cloud. The simulation results showed that the task caching strategy based on fine-grained migration can greatly reduce the energy consumption of mobile devices in the MEC environment.

scholarly journals Fine-Grained Energy Consumption Model of Servers Based on Task Characteristics in Cloud Data Center

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 27080-27090 ◽  
Author(s):  
Zhou Zhou ◽  
Jemal H. Abawajy ◽  
Fangmin Li ◽  
Zhigang Hu ◽  
Morshed U. Chowdhury ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Task Characteristics ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Fine Grained ◽  
Energy Consumption Model ◽  
Consumption Model

Privacy Preservation in Smart Grid Environment

2021 ◽  
pp. 1392-1410
Author(s):  
Muhammad Aminu Lawal ◽  
Syed Raheel Hassan
Keyword(s):  
Energy Consumption ◽  
Comparative Analysis ◽  
Smart Grid ◽  
Smart Grids ◽  
Privacy Preservation ◽  
User Privacy ◽  
Privacy And Security ◽  
Electricity Grid ◽  
Fine Grained ◽  
Comparison Table

Smart grids are conceived to ensure smarter generation, transmission, distribution, and consumption of electricity. It integrates the traditional electricity grid with information and communication technology. This enables a two-way communication among the smart grid entities, which translates to exchange of information about fine-grained user energy consumption between the smart grid entities. However, the flow of user energy consumption data may lead to the violation of user privacy. Inference on such data can expose the daily habits and types of appliances of users. Thus, several privacy preservation schemes have been proposed in the literature to ensure the privacy and security requirements of smart grid users. This chapter provides a review of some privacy preservation schemes. The schemes operational procedure, strengths, and weaknesses are discussed. A taxonomy, comparison table, and comparative analysis are also presented. The comparative analysis gives an insight on open research issues in privacy preservation schemes.

Application of an image management system in microscopy

1992 ◽  
Vol 50 (2) ◽  
pp. 1052-1053
Author(s):  
Richard S. Chemock
Keyword(s):  
Data Storage ◽  
Cost Savings ◽  
Image Data ◽  
Analytical Techniques ◽  
Operational Mode ◽  
Fine Grained ◽  
Image Recording ◽  
Primary Output ◽  
Capacity Data ◽  
Image Management System

One of the most common tasks in a typical analysis lab is the recording of images. Many analytical techniques (TEM, SEM, and metallography for example) produce images as their primary output. Until recently, the most common method of recording images was by using film. Current PS/2R systems offer very large capacity data storage devices and high resolution displays, making it practical to work with analytical images on PS/2s, thereby sidestepping the traditional film and darkroom steps. This change in operational mode offers many benefits: cost savings, throughput, archiving and searching capabilities as well as direct incorporation of the image data into reports.The conventional way to record images involves film, either sheet film (with its associated wet chemistry) for TEM or PolaroidR film for SEM and light microscopy. Although film is inconvenient, it does have the highest quality of all available image recording techniques. The fine grained film used for TEM has a resolution that would exceed a 4096x4096x16 bit digital image.

Use of fractals to describe microstructures of porous thick-film platinum electrodes

1992 ◽  
Vol 50 (1) ◽  
pp. 314-315
Author(s):  
Steven D. Toteda
Keyword(s):  
Fractal Dimension ◽  
Power Plants ◽  
Electrical Response ◽  
Cubic Phase ◽  
Platinum Electrodes ◽  
Fine Grained ◽  
Impedance Response ◽  
Platinum Particles ◽  
Energy Surfaces ◽  
Highly Porous

Zirconia oxygen sensors, in such applications as power plants and automobiles, generally utilize platinum electrodes for the catalytic reaction of dissociating O2 at the surface. The microstructure of the platinum electrode defines the resulting electrical response. The electrode must be porous enough to allow the oxygen to reach the zirconia surface while still remaining electrically continuous. At low sintering temperatures, the platinum is highly porous and fine grained. The platinum particles sinter together as the firing temperatures are increased. As the sintering temperatures are raised even further, the surface of the platinum begins to facet with lower energy surfaces. These microstructural changes can be seen in Figures 1 and 2, but the goal of the work is to characterize the microstructure by its fractal dimension and then relate the fractal dimension to the electrical response. The sensors were fabricated from zirconia powder stabilized in the cubic phase with 8 mol% percent yttria. Each substrate was sintered for 14 hours at 1200°C. The resulting zirconia pellets, 13mm in diameter and 2mm in thickness, were roughly 97 to 98 percent of theoretical density. The Engelhard #6082 platinum paste was applied to the zirconia disks after they were mechanically polished ( diamond). The electrodes were then sintered at temperatures ranging from 600°C to 1000°C. Each sensor was tested to determine the impedance response from 1Hz to 5,000Hz. These frequencies correspond to the electrode at the test temperature of 600°C.

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