Energy consumption analysis of parallel sorting algorithms running on multicore systems

2012 ◽  
Author(s):  
Ivan Zecena ◽  
Ziliang Zong ◽  
Rong Ge ◽  
Tongdan Jin ◽  
Zizhong Chen ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Multicore Systems ◽  
Parallel Sorting ◽  
Energy Consumption Analysis ◽  
Sorting Algorithms

scholarly journals Energy performance of parallel sort algorithms

2019 ◽  
Vol 48 (3) ◽  
pp. 487-498
Author(s):  
Zbigniew Marszalek
Keyword(s):  
Energy Consumption ◽  
Information Systems ◽  
Energy Performance ◽  
Parallel Sorting ◽  
Energy Consumption Analysis ◽  
Sorting Algorithms ◽  
Reduction Of Energy Consumption

This article shows the energy consumption analysis by parallel sorting algorithms. Sort algorithms are used in information systems and databases, to select and organize the information. The tests carried out confirm the reduction of energy consumption by using parallel sorting algorithms.

scholarly journals Experiments on Model-Based Software Energy Consumption Analysis Involving Sorting Algorithms

2020 ◽  
Vol 27 (3) ◽  
pp. 72-83
Author(s):  
Danilo Silva Alves ◽  
Oseias Ayres Ferreira ◽  
Lucio Mauro Duarte ◽  
Davi Silva ◽  
Paulo Henrique Maia
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Measurement Tool ◽  
Analysis Tool ◽  
Related Information ◽  
Energy Consumption Analysis ◽  
Sorting Algorithms ◽  
Software Energy Consumption ◽  
Energy Information ◽  
Efficient Software

Although energy has become an important aspect in software development, little support exists for creating energy-efficient programs. One reason for that is the lack of abstractions and tools to enable the analysis of relevant properties involving energy consumption. This paper presents the results of some experiments involving the gathering, modelling, and analysis of energy-related information, in particular, the costs of executing certain parts of a software. We combine some existing free and open-source tools to carry out the experiments, extending one of them to handle energy information. Our experiments consider a comparison of energy consumption of Java implementations of the Bubble Sort, Insertion Sort and Selection Sort algorithms using different data structures. We show how to combine an energy measurement tool and a model analysis tool to carry such a comparison. Based on this support and on our experiments, we believe this is a first step to allow developers to start creating more energy-efficient software.

scholarly journals Practical Model for Energy Consumption Analysis of Omnidirectional Mobile Robot

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Load Capacity ◽  
Working Environment ◽  
Energy Consumption Analysis ◽  
Mecanum Wheel ◽  
Save Energy ◽  
Energy Consumption Modeling ◽  
Robot Platform

The four-wheeled Mecanum robot is widely used in various industries due to its maneuverability and strong load capacity, which is suitable for performing precise transportation tasks in a narrow environment. While the Mecanum wheel robot has mobility, it also consumes more energy than ordinary robots. The power consumed by the Mecanum wheel mobile robot varies enormously depending on their operating regimes and environments. Therefore, only knowing the working environment of the robot and the accurate power consumption model can we accurately predict the power consumption of the robot. In order to increase the applicable scenarios of energy consumption modeling for Mecanum wheel robots and improve the accuracy of energy consumption modeling, this paper focuses on various factors that affect the energy consumption of the Mecanum wheel robot, such as motor temperature, terrain, the center of gravity position, etc. The model is derived from the kinematic and kinetic model combined with electrical engineering and energy flow principles. The model has been simulated in MATLAB and experimentally validated with the four-wheeled Mecanum robot platform in our lab. Experimental results show that the accuracy of the model reached 95%. The results of energy consumption modeling can help robots save energy by helping them to perform rational path planning and task planning.

scholarly journals Energy Consumption Analysis and Characterization of Healthcare Facilities in the United States

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3775 ◽  
Author(s):  
Khaled Bawaneh ◽  
Farnaz Ghazi Nezami ◽  
Md. Rasheduzzaman ◽  
Brad Deken
Keyword(s):  
United States ◽  
Energy Consumption ◽  
Energy Intensity ◽  
The United States ◽  
High Energy ◽  
Total Energy Consumption ◽  
Healthcare Facilities ◽  
Energy Consumption Analysis ◽  
Consumption Data ◽  
End Use

Healthcare facilities in the United States account for 4.8% of the total area in the commercial sector and are responsible for 10.3% of total energy consumption in this sector. The number of healthcare facilities increased by 22% since 2003, leading to a 21% rise in energy consumption and an 8% reduction in energy intensity per unit of area (544.8 kWh/m2). This study provides an analytical overview of the end-use energy consumption data in healthcare systems for hospitals in the United States. The energy intensity of the U.S. hospitals ranges from 640.7 kWh/m2 in Zone 5 (very hot) to 781.1 kWh/m2 in Zone 1 (very cold), with an average of 738.5 kWh/m2. This is approximately 2.6 times higher than that of other commercial buildings. High energy intensity in the healthcare facilities, particularly in hospitals, along with energy costs and associated environmental concerns make energy analysis crucial for this type of facility. The proposed analysis shows that U.S. healthcare facilities have higher energy intensity than those of most other countries, especially the European ones. This necessitates the adoption of more energy-efficient approaches to the infrastructure and the management of healthcare facilities in the United States.

Model Based Energy Consumption Analysis of Wireless Cyber Physical Systems

2017 ◽  
Vol 90 (8-9) ◽  
pp. 1191-1204 ◽  
Author(s):  
Ping Wang ◽  
Jing Liu ◽  
Jinlong Lin ◽  
Chao-Hsien Chu
Keyword(s):  
Energy Consumption ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Model Based ◽  
Energy Consumption Analysis
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