The impact of workload variability on the energy efficiency of large-scale heterogeneous distributed systems

2018 ◽  
Vol 89 ◽  
pp. 135-143 ◽  
Author(s):  
Georgios L. Stavrinides ◽  
Helen D. Karatza
Keyword(s):  
Energy Efficiency ◽  
Distributed Systems ◽  
Large Scale ◽  
Heterogeneous Distributed Systems ◽  
The Impact

scholarly journals Effectiveness of a Power Factor Correction Policy in Improving the Energy Efficiency of Large-Scale Electricity Users in Ghana

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2582 ◽  
Author(s):  
Samuel Lotsu ◽  
Yuichiro Yoshida ◽  
Katsufumi Fukuda ◽  
Bing He
Keyword(s):  
Energy Efficiency ◽  
Power Factor ◽  
Large Scale ◽  
Regression Discontinuity ◽  
Power Factor Correction ◽  
Energy Crisis ◽  
Regression Discontinuity Design ◽  
The Government ◽  
Power Factor Improvement ◽  
The Impact

Confronting an energy crisis, the government of Ghana enacted a power factor correction policy in 1995. The policy imposes a penalty on large-scale electricity users, namely, special load tariff (SLT) customers of the Electricity Company of Ghana (ECG), whose power factor is below 90%. This paper investigates the impact of this policy on these firms’ power factor improvement by using panel data from 183 SLT customers from 1994 to 1997 and from 2012. To avoid potential endogeneity, this paper adopts a regression discontinuity design (RDD) with the power factor of the firms in the previous year as a running variable, with its cutoff set at the penalty threshold. The result shows that these large-scale electricity users who face the penalty because their power factor falls just short of the threshold are more likely to improve their power factor in the subsequent year, implying that the power factor correction policy implemented by Ghana’s government is effective.

scholarly journals A survey on techniques for improving the energy efficiency of large-scale distributed systems

2014 ◽  
Vol 46 (4) ◽  
pp. 1-31 ◽  
Author(s):  
Anne-Cecile Orgerie ◽  
Marcos Dias de Assuncao ◽  
Laurent Lefevre
Keyword(s):  
Energy Efficiency ◽  
Distributed Systems ◽  
Large Scale

Adaptive Threshold Based Scheduler for Batch of Independent Jobs for Cloud Computing System

2021 ◽  
pp. 2246-2266
Author(s):  
TAJ ALAM ◽  
PARITOSH DUBEY ◽  
ANKIT KUMAR
Keyword(s):  
Cloud Computing ◽  
Distributed Systems ◽  
High Performance ◽  
Large Scale ◽  
Real Life ◽  
Interval Estimation ◽  
Computing System ◽  
Adaptive Threshold ◽  
Batch Simulation ◽  
Heterogeneous Distributed Systems

Distributed systems are efficient means of realizing high-performance computing (HPC). They are used in meeting the demand of executing large-scale high-performance computational jobs. Scheduling the tasks on such computational resources is one of the prime concerns in the heterogeneous distributed systems. Scheduling jobs on distributed systems are NP-complete in nature. Scheduling requires either heuristic or metaheuristic approach for sub-optimal but acceptable solutions. An adaptive threshold-based scheduler is one such heuristic approach. This work proposes adaptive threshold-based scheduler for batch of independent jobs (ATSBIJ) with the objective of optimizing the makespan of the jobs submitted for execution on cloud computing systems. ATSBIJ exploits the features of interval estimation for calculating the threshold values for generation of efficient schedule of the batch. Simulation studies on CloudSim ensures that the ATSBIJ approach works effectively for real life scenario.

Energy efficiency in large-scale distributed systems

2012 ◽  
Vol 28 (5) ◽  
pp. 743-744
Author(s):  
Tuan Anh Trinh ◽  
Helmut Hlavacs ◽  
Domenico Talia
Keyword(s):  
Energy Efficiency ◽  
Distributed Systems ◽  
Large Scale

ERIDIS: ENERGY-EFFICIENT RESERVATION INFRASTRUCTURE FOR LARGE-SCALE DISTRIBUTED SYSTEMS

2011 ◽  
Vol 21 (02) ◽  
pp. 133-154 ◽  
Author(s):  
ANNE-CECILE ORGERIE ◽  
LAURENT LEFEVRE
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Distributed Systems ◽  
Energy Efficient ◽  
Large Scale ◽  
Generic Framework ◽  
Peer To Peer Systems ◽  
Dedicated Networks ◽  
Electrical Consumption ◽  
Hardware Designs

At the age of petascale machines, cloud computing and peer-to-peer systems, large-scale distributed systems need an ever-increasing amount of energy. These systems urgently require effective and scalable solutions to manage and limit their electrical consumption. As of now, most efforts are focused on energy-efficient hardware designs. Thus, the challenge is to coordinate all these low-level improvements at the middleware level to improve the energy efficiency of the overall systems. Resource-management solutions can indeed benefit from a broader view to pool the resources and to share them according to the needs of each user. In this paper, we propose ERIDIS, an Energy-efficient Reservation Infrastructure for large-scale DIstributed Systems. It provides a unified and generic framework to manage resources from Grids, Clouds and dedicated networks in an energy-efficient way.

scholarly journals A Study on the Impact of Nodes Density on the Energy Consumption of LoRa

2021 ◽  
Vol 15 (14) ◽  
pp. 157
Author(s):  
Aizat Faiz Ramli ◽  
Muhammad Ikram Shabry ◽  
Mohd Azlan Abu ◽  
Hafiz Basarudin
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Low Power ◽  
Large Scale ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Area Network ◽  
Wide Area Network ◽  
Consumption Ratio ◽  
The Impact

LoRaWAN is one of the leading Low power wide area network (LPWAN) LPWAN technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio ECR to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the nodes density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11.

scholarly journals Analysis of the Impact of Residential Property and Equipment on Building Energy Efficiency and Consumption—A Data Mining Approach

2020 ◽  
Vol 10 (10) ◽  
pp. 3589 ◽  
Author(s):  
Mahsa Nazeriye ◽  
Abdorrahman Haeri ◽  
Francisco Martínez-Álvarez
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Large Scale ◽  
Building Energy Efficiency ◽  
Data Set ◽  
Residential Homes ◽  
Improve Energy Efficiency ◽  
Data Mining Approach ◽  
The Impact

Human living could become very difficult due to a lack of energy. The household sector plays a significant role in energy consumption. Trying to optimize and achieve efficient energy consumption can lead to large-scale energy savings. The aim of this paper is to identify the equipment and property affecting energy efficiency and consumption in residential homes. For this purpose, a hybrid data-mining approach based on K-means algorithms and decision trees is presented. To analyze the approach, data is modeled once using the approach and then without it. A data set of residential homes of England and Wales is arranged in low, medium and high consumption clusters. The C5.0 algorithm is run on each cluster to extract factors affecting energy efficiency. The comparison of the modeling results, and also their accuracy, prove that the approach employed has the ability to extract the findings with greater accuracy and detail than in other cases. The installation of boilers, using cavity walls, and installing insulation could improve energy efficiency. Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results.

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