Economic Aspects of Green ICT

Fernández, Héctor; Procaccianti, Giuseppe; Lago, Patricia

doi:10.1007/978-3-319-08581-4_5

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…In order to ease the adoption of Green IT best practices, we developed a number of tools [15], [21] that provide insights and estimations on their economic and environmental impacts. We also have an online library of such practices 4 that can be used as a knowledge base for practitioners who want to have a concrete overview of actionable strategies for reducing their carbon footprint -and energy bill.…”

Section: Discussionmentioning

confidence: 99%

Energy Efficiency and Power Measurements: an Industrial Survey

Procaccianti¹,

Routsis²

2016

Proceedings of ICT for Sustainability 2016

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Context. In the last few years, the energy consumption of data centers increased substantially. Currently, energy costs are the main expenditure in data center ownership. This creates the need for more precise quantitative metrics and measurements for energy management in the data center industry. However, despite the effort of multiple public and private agencies to address this problem, there is still little knowledge among practitioners on such topic.Aim. The goal of our work is to investigate the state-ofthe-Practice of power measurements and energy efficiency techniques in the data center industry.Method. We interviewed 7 practitioners and stakeholders from 4 companies of different size. We used semi-structured interviews of 1 hour as our research methodology.Results. Our results show that all the companies we interviewed measure power consumption, but only up to racklevel granularity. Several energy efficiency practices have been adopted, with positive results. However, the only metric considered to evaluate the impact of such practices is the Power Usage Effectiveness (PUE), although the representativity of such metric has been widely questioned in scientific literature and by our interviewees as well. We observed a lack of awareness with respect to other metrics, which could also be used to share such information across different stakeholders (e.g. suppliers, infrastructure managers, customers).Conclusions. Our contribution motivates further efforts from the data center industry to go beyond the PUE and adopt more advanced metrics to evaluate the energy efficiency of their data centers. This is a required step to ensure that real improvements are made towards sustainability goals.

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Section: Discussionmentioning

confidence: 99%

Energy Efficiency and Power Measurements: an Industrial Survey

Procaccianti¹,

Routsis²

2016

Proceedings of ICT for Sustainability 2016

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“…However, theoretically, power usage effectiveness is approaching, future efficiency gains will be minor and new approaches are needed. For example, most Green ICT practices do not yet particularly tackle software-specific aspects to improve sustainability [88] as we have proposed in this paper. In recent times, artificial intelligence has been employed for reducing power consumption in data centers [89].…”

Section: Sustainability Findingsmentioning

confidence: 99%

The Effect of Green Software: A Study of Impact Factors on the Correctness of Software

et al. 2018

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Unfortunately, sustainability is an issue very poorly used when developing software and hardware systems. Lately, and in order to contribute to the earth sustainability, a new concept emerged named Green software which is computer software that can be developed and used efficiently and effectively with minimal or no impact to the environment. Currently, new teaching methods based on students’ learning process are being developed in the European Higher Education Area. Most of them are oriented to promote students’ interest in the course’s contents and offer personalized feedback. Online judging is a promising method for encouraging students’ participation in the e-learning process, although it still has to be researched and developed to be widely used and in a more efficient way. The great amount of data available in an online judging tool provides the possibility of exploring some of the most indicative attributes (e.g., running time, memory) for learning programming concepts, techniques and languages. So far, the most applied methods for automatically gathering information from the judging systems are based on statistical methods and, although providing reasonable correlations, these methods have not been proven to provide enough information for predicting grades when dealing with a huge amount of data. Therefore, the great novelty of this paper is to develop a data mining approach to predict program correctness as well as the grades of the students’ practices. For this purpose, powerful data mining technologies taken from the artificial intelligence domain have been used. In particular, in this study, we have used logistic regression, decision trees, artificial neural network and support vector machines; which have been properly identified as the most suitable ones for predicting activities in the e-learning domains. The results have achieved an accuracy of around 74%, both in the prediction of the program correctness as well as in the practice grades’ prediction. Another relevant issue provided in this paper is a comparison among these four techniques to obtain the best accuracy in predicting grades based on the availability of data as well as their taxonomy. The Decision Trees classifier has obtained the best confusion matrix, and time and memory efficiency were identified as the most important predictor variables. In view of these results, we can conclude that the development of green software leads programmers to implement correct software.

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“…As indicated by the investigation by Corbett [25], the most ordinarily referred to driver for reusing Green IT practices is sparing expenses. Particularly in times of monetary emergency, cost lessening turns into the most essential financial goal [1,26] of numerous organizations. On the off chance that green practices don't prompt an express (and critical) diminishment of costs, natural objectives are regularly viewed as a pleasant discretionary reward as opposed to an unquestionable target [27].…”

Section: B Economic Sustainabilitymentioning

confidence: 99%

Exploring Potential Factors in Green and Sustainable Software Product

Raisian

Yahaya

Deraman

2018

JOIV : Int. J. Inform. Visualization

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Abstract-software engineering is a principle role of our activity in social and economic life. Software engineers are starting to comprehend the significance of designing sustainability regarding software processes. The field of sustainable and green software and green software engineering is still young. Thus, in modern society, researches effort is mainly focused on green and sustainable software engineering itself. In other words, the aim of this study at hand aims an in-depth understanding of the related potential factors for the purpose of improving the recently reluctant trend of sustainability dimension in green software based on life cycle of green software product process. To reach this purpose, this study is reviewed latest research and used conceptual model. A conceptual model is rendered demonstrating the consolidated life cycles of sustainable product and principle sustainable measurement dimensions, for example, energy or information efficiency, low cost, Resource efficiency, Waste reduction, Equality support and human health.

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Economic Aspects of Green ICT

Cited by 5 publications

References 15 publications

Energy Efficiency and Power Measurements: an Industrial Survey

Energy Efficiency and Power Measurements: an Industrial Survey

The Effect of Green Software: A Study of Impact Factors on the Correctness of Software

Exploring Potential Factors in Green and Sustainable Software Product

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