scholarly journals Green software engineering: the curse of methodology

2015 ◽  
Author(s):  
Abram Hindle
Keyword(s):  
Energy Consumption ◽  
Software Engineering ◽  
Energy Use ◽  
Natural Sciences ◽  
Physical Measurement ◽  
Green It ◽  
Physical Measurements ◽  
Current State ◽  
Green Software ◽  
Software Energy Consumption

Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering. With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering. Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue. Thus in this work we discuss the current state of software energy consumption, and where will it go.

scholarly journals Green software engineering: the curse of methodology

2016 ◽  
Author(s):  
Abram Hindle
Keyword(s):  
Energy Consumption ◽  
Software Engineering ◽  
Energy Use ◽  
Natural Sciences ◽  
Physical Measurement ◽  
Green It ◽  
Physical Measurements ◽  
Current State ◽  
Green Software ◽  
Software Energy Consumption

Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering. With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering. Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue. Thus in this work we discuss the current state of software energy consumption, and where will it go.

scholarly journals Green software engineering: the curse of methodology

2016 ◽  
Author(s):  
Abram Hindle
Keyword(s):  
Energy Consumption ◽  
Software Engineering ◽  
Energy Use ◽  
Natural Sciences ◽  
Physical Measurement ◽  
Green It ◽  
Physical Measurements ◽  
Current State ◽  
Green Software ◽  
Software Energy Consumption

Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering. With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering. Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue. Thus in this work we discuss the current state of software energy consumption, and where will it go.

scholarly journals Development of a model for assessing energy consumption of a system

2021 ◽  
Vol 2134 (1) ◽  
pp. 012012
Author(s):  
Gcinizwe Dlamini ◽  
Artem Kruglov ◽  
Xavier Vasquez ◽  
Vyacheslav Pavlov
Keyword(s):  
Machine Learning ◽  
Operating System ◽  
Energy Consumption ◽  
Estimation Model ◽  
Software Products ◽  
Current State ◽  
Recent Trends ◽  
Green Software ◽  
Ict Industry ◽  
Precise Assessment

Abstract The recent trends in the ICT industry are related to the development and implementation of green software products and practices. The way to seek for energy efcient solutions starts from the proper and precise assessment of the current state of the system in hand. In this paper we present the software-based approach to the energy efciency assessment. We propose machine learning based approach to estimate energy consumed by a computer system. We evaluated our approach on datasets extracted from systems running on Linux and Windows operating system. Using MSE, MAE and R2 our energy consumption estimation model reached 0.0007, 0.0104, 0.9214, respectively.

Rationale and Design Considerations for a Semantic Mediator in Health Information Systems

1998 ◽  
Vol 37 (04/05) ◽  
pp. 518-526 ◽  
Author(s):  
D. Sauquet ◽  
M.-C. Jaulent ◽  
E. Zapletal ◽  
M. Lavril ◽  
P. Degoulet
Keyword(s):  
Information Systems ◽  
Software Engineering ◽  
Health Information ◽  
Rapid Development ◽  
Heterogeneous Systems ◽  
Health Information Systems ◽  
Semantic Interoperability ◽  
Point Of View ◽  
Current State ◽  
Engineering Environment

AbstractRapid development of community health information networks raises the issue of semantic interoperability between distributed and heterogeneous systems. Indeed, operational health information systems originate from heterogeneous teams of independent developers and have to cooperate in order to exchange data and services. A good cooperation is based on a good understanding of the messages exchanged between the systems. The main issue of semantic interoperability is to ensure that the exchange is not only possible but also meaningful. The main objective of this paper is to analyze semantic interoperability from a software engineering point of view. It describes the principles for the design of a semantic mediator (SM) in the framework of a distributed object manager (DOM). The mediator is itself a component that should allow the exchange of messages independently of languages and platforms. The functional architecture of such a SM is detailed. These principles have been partly applied in the context of the HEllOS object-oriented software engineering environment. The resulting service components are presented with their current state of achievement.

scholarly journals Evaluation of CO2 emissions and energy use with different container terminal layouts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Arif Budiyanto ◽  
Muhammad Hanzalah Huzaifi ◽  
Simon Juanda Sirait ◽  
Putu Hangga Nan Prayoga
Keyword(s):  
Energy Efficiency ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Statistical Analysis ◽  
Energy Use ◽  
Container Terminal ◽  
Container Terminals ◽  
Future Planning ◽  
Container Handling

AbstractSustainable development of container terminals is based on energy efficiency and reduction in CO2 emissions. This study estimated the energy consumption and CO2 emissions in container terminals according to their layouts. Energy consumption was calculated based on utility data as well as fuel and electricity consumptions for each container-handling equipment in the container terminal. CO2 emissions were estimated using movement modality based on the number of movements of and distance travelled by each container-handling equipment. A case study involving two types of container terminal layouts i.e. parallel and perpendicular layouts, was conducted. The contributions of each container-handling equipment to the energy consumption and CO2 emissions were estimated and evaluated using statistical analysis. The results of the case study indicated that on the CO2 emissions in parallel and perpendicular layouts were relatively similar (within the range of 16–19 kg/TEUs). These results indicate that both parallel and perpendicular layouts are suitable for future ports based on sustainable development. The results can also be used for future planning of operating patterns and layout selection in container terminals.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3864
Author(s):  
Qiucheng Li ◽  
Jiang Hu ◽  
Bolin Yu
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Decomposition Analysis ◽  
Theil Index ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Index Method ◽  
Inequality Measures ◽  
Influencing Mechanism ◽  
Per Capita

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.

scholarly journals Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4046 ◽  
Author(s):  
Sooyoun Cho ◽  
Jeehang Lee ◽  
Jumi Baek ◽  
Gi-Seok Kim ◽  
Seung-Bok Leigh
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Simulation Analysis ◽  
Residential Buildings ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Building Energy ◽  
Major Effect ◽  
Measuring Instruments ◽  
Building Energy Consumption

Although the latest energy-efficient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three different methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major effect on energy consumption and revealed that these key variables alone, not the default values of many different items in simulation analysis, can ensure the reliable prediction of energy consumption.

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