scholarly journals Big Steps Towards Query Eco-Processing - Thinking Smart

2021 ◽  
Vol Volume 34 - 2020 - Special... ◽  
Author(s):  
Simon Pierre Dembele ◽  
Ladjel Bellatreche ◽  
Carlos Ordonez ◽  
Nabil Gmati ◽  
Mathieu Roche ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Cost Models ◽  
It Systems ◽  
Environmentally Responsible ◽  
International Audience ◽  
Query Optimizers ◽  
Carbon Dioxide Co2 ◽  
Time And Energy ◽  
Sensitive Parameters

Soumission à Episciences International audience Computers and electronic machines in businesses consume a significant amount of electricity, releasing carbon dioxide (CO2), which contributes to greenhouse gas emissions. Energy efficiency is a pressing concern in IT systems, ranging from mobile devices to large servers in data centers, in order to be more environmentally responsible. In order to meet the growing demands in the awareness of excessive energy consumption, many initiatives have been launched on energy efficiency for big data processing covering electronic components, software and applications. Query optimizers are one of the most power consuming components of a DBMS. They can be modified to take into account the energetical cost of query plans by using energy-based cost models with the aim of reducing the power consumption of computer systems. In this paper, we study, describe and evaluate the design of three energy cost models whose values of energy sensitive parameters are determined using the Nonlinear Regression and the Random Forests techniques. To this end, we study in depth the operating principle of the selected DBMS and present an analysis comparing the performance time and energy consumption of typical queries in the TPC benchmark. We perform extensive experiments on a physical testbed based on PostreSQL, MontetDB and Hyrise systems using workloads generatedusing our chosen benchmark to validate our proposal. Les ordinateurs et les machines électroniques des entreprises consomment une quantité importante d’électricité, libérant ainsi du dioxyde de carbone (CO2), qui contribue aux émissions de gaz à effet de serre. L’efficacité énergétique est une préoccupation urgente dans les systèmesinformatiques, partant des équipements mobiles aux grands serveurs dans les centres de données, afin d’être plus respectueux envers l’environnement. Afin de répondre aux exigences croissantes en matière de sensibilisation à l’utilisation excessive de l’énergie, de nombreuses initiatives ont été lancées sur l’efficacité énergétique pour le traitement des données massives couvrant les composantsélectroniques, les logiciels et les applications. Les optimiseurs de requêtes sont l’un des composants les plus énergivores d’un SGBD. Ils peuvent être modifiés pour prendre en compte le coût énergétique des plans des requêtes à l’aide des modèles de coût énergétiques intégrés dans l’optimiseur dans le but de réduire la consommation électrique des systèmes informatiques. Dans cet article, nousétudions, décrivons et évaluons la conception de trois modèles de coût énergétique dont les valeurs des paramètres sensibles à l’énergie sont définis en utilisant la technique de la Régression non linéaire et la technique des forêts aléatoires. Pour ce fait, nous menons une étude approfondie du principe de fonctionnement des SGBD choisis et présentons une analyse des performances en termes de temps et énergie sur des requêtes typiques du benchmarks TPC-H. Nous effectuons des expériences approfondies basées sur les systèmes PostgreSQL, MonetDB et Hyrise en utilisant un jeu de données généré à partir du benchmarks TPC-H afin de valider nos propositions.

scholarly journals An Energy Consumption Approach to Estimate Air Emission Reductions in Container Shipping

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 278
Author(s):  
Ernest Czermański ◽  
Giuseppe T. Cirella ◽  
Aneta Oniszczuk-Jastrząbek ◽  
Barbara Pawłowska ◽  
Theo Notteboom
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Early Stage ◽  
Management Plan ◽  
Policy Formulation ◽  
Container Shipping ◽  
Shipping Industry ◽  
Emission Reductions ◽  
Energy Efficiency Design Index ◽  
Carbon Dioxide Co2

Container shipping is the largest producer of emissions within the maritime shipping industry. Hence, measures have been designed and implemented to reduce ship emission levels. IMO’s MARPOL Annex VI, with its future plan of applying Tier III requirements, the Energy Efficiency Design Index for new ships, and the Ship Energy Efficiency Management Plan for all ships. To assist policy formulation and follow-up, this study applies an energy consumption approach to estimate container ship emissions. The volumes of sulphur oxide (SOx), nitrous oxide (NOx), particulate matter (PM), and carbon dioxide (CO2) emitted from container ships are estimated using 2018 datasets on container shipping and average vessel speed records generated via AIS. Furthermore, the estimated reductions in SOx, NOx, PM, and CO2 are mapped for 2020. The empirical analysis demonstrates that the energy consumption approach is a valuable method to estimate ongoing emission reductions on a continuous basis and to fill data gaps where needed, as the latest worldwide container shipping emissions records date back to 2015. The presented analysis supports early-stage detection of environmental impacts in container shipping and helps to determine in which areas the greatest potential for emission reductions can be found.

Maximizing Coverage for Mobile Robots While Conserving Energy

2012 ◽  
Author(s):  
John Broderick ◽  
Dawn Tilbury ◽  
Ella Atkins
Keyword(s):  
Optimal Control ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Mobile Robots ◽  
Spanning Tree ◽  
Trade Offs ◽  
Tree Methods ◽  
Reduce Energy Consumption ◽  
Point To Point ◽  
Time And Energy

This paper presents a method to compare area coverage paths in the context of energy efficiency. We examine cover-age paths created from the Boustrophedon Decomposition and Spanning Tree methods in an optimal control setting. Our cost function weights the force inputs to drive the robot and the currently uncovered region. We derive an optimal traversal of the path in a point-to-point manner. In particular, we introduce a meas function that represents the percentage of the area that is still to be visited. The effect of meas on the optimal traversal is derived. Trade-offs between area covered versus the time and energy required are presented. A simple trajectory modification allows the vehicle to continue moving through a turn to reduce energy consumption.

Rail Transportation Energy Efficiency-Oriented Technologies

2012 ◽  
Author(s):  
Pamela E. Alexander
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Systems ◽  
New Technologies ◽  
Rail Transportation ◽  
Transportation Energy ◽  
Increase Energy Efficiency ◽  
Rail Systems ◽  
Sustainability Initiatives ◽  
Carbon Dioxide Co2

Rail transportation is playing a very important role in the effort to keep the world’s expanding major cities safe and mobile. Travel by rail can move people and cargo with higher levels of energy efficiency, greater safety, lower cost and greater reliability than any other mode of transportation. On average, trips by train can generate between one third and one fifth of the carbon dioxide (CO2) produced by the equivalent automobile or airplane travel. Environmental awareness plus reduced operating costs are primary considerations in decision making for new transit programs around the globe. Energy consumption is a major part of rail operation costs and has been at the focus of rail systems sustainability initiatives. The majority of energy consumed by metropolitan and urban rail systems is used to move the trains. In recent years, energy saving technologies for rail vehicle power systems have been implemented on many rail systems worldwide. Improving railway energy efficiency results in not only a reduction in energy consumption and cost, but also a reduction in pollution due to power generation. In an effort to promote environmental quality and energy efficiency, energy usage in rail systems is analyzed to identify new technologies, developments, and procedures for increased efficiency. This paper provides an overview of the various strategies and solutions used to increase energy efficiency in rail systems and highlights the key technologies needed for their implementation.

scholarly journals Architecture and Mechanisms of Energy Auto-Tuning

2012 ◽  
pp. 45-73 ◽  
Author(s):  
Sebastian Götz ◽  
Claas Wilke ◽  
Sebastian Cech ◽  
Uwe Aßmann
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Data Extraction ◽  
Optimization Technique ◽  
Functional Requirements ◽  
Software Applications ◽  
It Systems ◽  
Data Extraction Tool ◽  
Auto Tuning ◽  
The Cost

Energy efficiency of IT infrastructures has been a well-discussed research topic for several decades. The resulting approaches include hardware optimizations, resource management in operating systems, network protocols, and many more. The approach the authors present in this chapter is a self-optimization technique for IT infrastructures, which takes hard- and software components as well as users of software applications into account. It is able to ensure minimal energy consumption for a user request along with a set of non-functional requirements (e.g., the refresh rate of a data extraction tool). To optimize the ratio between utility of end users and the cost in terms of energy consumption, the system needs inherent variability leading to differentiated energy profiles and mechanisms to reconfigure the system at runtime. The authors present their approach called Energy Auto-Tuning (EAT) comprised of these mechanisms and an architecture which automatically tunes the energy efficiency of IT systems.

scholarly journals Estimating the Rebound Effect of the U.S. Road Freight Transport

2021 ◽  
pp. 036119812199149
Author(s):  
A. Latif Patwary ◽  
T. Edward Yu ◽  
Burton C. English ◽  
David W. Hughes ◽  
Seong-Hoon Cho
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Policy Development ◽  
Rebound Effect ◽  
The United States ◽  
Cost Models ◽  
Total Energy Consumption ◽  
Price Response ◽  
Road Freight ◽  
The U.S

The United States (U.S.) road freight sector has continued to grow over recent decades. Growth in road freight could result in more fuel consumption and hence increased greenhouse gas emissions. Policymakers have attempted to manage the growth of energy usage through improved fuel economy based on technological advances. However, such improvements may not lead to anticipated goals because of the rebound effect, where improvements in energy efficiency trigger more travel and energy consumption that offsets energy savings. Thus, this study aims to determine the potential rebound effect from improved energy efficiency in the U.S. road freight sector. Eight fuel cost models are applied and asymmetric price response is incorporated in estimating the U.S. road freight sector’s rebound effect from 1980 to 2016. In addition, a recently developed data envelopment analysis is applied to determine the annual rebound effect in the road freight sector. The results suggest that, after accounting for the asymmetric price response, the average rebound effect of the U.S. road freight sector ranges from 6.9% to 8.8%, a level considerably less than that found for several industrialized countries and emerging economies. However, a considerable increase in the rebound effect has been seen in more recent years. The findings suggest that overlooking the rebound effect in environmental policies could impede the goal of reducing total energy consumption and accompanying emissions. Policymakers should incorporate the rebound effect from efficiency enhancement in policy development and utilize some potential programs to reduce the adverse influence of rebound effect in related policies.

scholarly journals Scheduling Parallel Work ow Applications with Energy-Aware on a Cloud Platform

1970 ◽  
Vol 9 (1) ◽  
pp. 11-21
Author(s):  
Thanawut Thanavanich ◽  
Putchong Uthayopas
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Critical Path ◽  
Operating Cost ◽  
Computing System ◽  
Cloud Platform ◽  
Energy Aware ◽  
Cloud Computing System ◽  
Best Execution ◽  
Time And Energy

An inefficient energy consumption of computing resources in a large cloud datacenter is a very important issue since the energy cost is now a major part of the operating expense. In this paper, the challenge of scheduling a parallel application on a cloud platform to achieve both time and energy efficiency is addressed by two new proposed algorithms Enhancing Heterogonous Earliest Finish Time (EHEFT) and Enhancing Critical Path on a Processor (ECPOP). The objective of these two algorithms is to reduce the energy consumption while achieving the best execution makespan. The algorithms use a metric that identifies and turns off the inefficient processors to reduce energy consumption. Then, the application tasks are rescheduled on fewer processors to obtain better energy efficiency. The experimental results from the simulation using real-world application workload show that the proposed algorithms not only reduce the energy consumption, but also maintain an acceptable scheduling quality. Thus, these algorithms can be employed to substantially reduce the operating cost in a large cloud computing system.

scholarly journals Effect of Pretreatments on Convective and Infrared Drying Kinetics, Energy Consumption and Quality of Terebinth

2021 ◽  
Vol 11 (16) ◽  
pp. 7672
Author(s):  
Yousef Abbaspour-Gilandeh ◽  
Mohammad Kaveh ◽  
Hamideh Fatemi ◽  
Esmail Khalife ◽  
Dorota Witrowa-Rajchert ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Bioactive Compounds ◽  
Specific Energy Consumption ◽  
Moisture Diffusion ◽  
Drying Kinetics ◽  
Convective Drying ◽  
Drying Time ◽  
Time And Energy

This study is focused on the influence of convective drying (50, 60, and 70 °C) and infrared (IR) power (250, 500, and 750 W) on the drying kinetics, the specific energy consumption of terebinth drying as well as quality and bioactive compounds upon various pretreatments such as ultrasound (US), blanching (BL), and microwave (MW). Compared to convective drying, IR drying decreased more the drying time and energy consumption (SEC). Application of higher IR powers and air temperatures accelerated the drying process at lower energy consumption (SEC) and higher energy efficiency and moisture diffusion. Terebinth dried by a convective dryer at 60 °C with US pretreatment showed a better color compared to other samples. It also exhibited the polyphenol and flavonoid content of 145.35 mg GAE/g d.m. and 49.24 mg QE/g d.m., respectively, with color variations of 14.25 and a rehydration rate of 3.17. The proposed pretreatment methods significantly reduced the drying time and energy consumption, and from the other side it increased energy efficiency, bioactive compounds, and quality of the dried samples (p < 0.01). Among the different pretreatments used, microwave pretreatment led to the best results in terms of the drying time and SEC, and energy efficiency. US pretreatment showed the best results in terms of preserving the bioactive compounds and the general appearance of the terebinth.

Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

2020 ◽  
Vol 14 ◽  
Author(s):  
M. Sivaram ◽  
V. Porkodi ◽  
Amin Salih Mohammed ◽  
S. Anbu Karuppusamy
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Artificial Bee Colony ◽  
Trust Model ◽  
Sensor Nodes ◽  
Remote Areas ◽  
Bee Colony ◽  
Important Concern ◽  
Wide Range ◽  
Iot Devices

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities help to reduce the constraint demands of the current security protocols. Aim: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem in IoT and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, energy efficiency in WSNs has been an important concern. Methods: Hence, in this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

scholarly journals Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model

2021 ◽  
Author(s):  
Ahmad Reza Jafarian-Moghaddam
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Pollutant Emissions ◽  
Scheduling Problems ◽  
Train Scheduling ◽  
Multi Objective ◽  
Consumption Ratio ◽  
Proposed Model ◽  
Objective Model ◽  
Time And Energy

AbstractSpeed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

Sign in / Sign up

Export Citation Format

Share Document