Energy Efficiency in the ICT - Profiling Power Consumption in Desktop Computer Systems

Energy awareness in the ICT has become an important issue. Focusing on software, recent work suggested the existence of a relationship between power consumption, software configuration and usage patterns in computer systems. The aim of this work was collecting and analysing power consumption data of general-purpose computer systems, simulating common usage scenarios, in order to extract a power consumption profile for each scenario. We selected two desktop systems of different generations as test machines. Meanwhile, we developed 11 usage scenarios, and conducted several test runs of them, collecting power consumption data by means of a power meter. Our analysis resulted in an estimation of a power consumption value for each scenario and software application used, obtaining that each single scenario introduced an overhead from 2 to 11 Watts, which corresponds to a percentage increase that can reach up to 20% on recent and more powerful systems. We determined that software and its usage patterns impact consistently on the power consumption of computer systems. Further work will be devoted to evaluate how power consumption is affected by the usage of specific system resource

Profiling Power Consumption on Desktop Computer Systems

Background. Energy awareness in the ICT has become an important issue: ICT is both a key player in energy efficiency, and a power drainer. Focusing on software, recent work suggested the existence of a relationship between power consumption, software configuration and usage patterns in computer systems. Aim. The aim of this work was collecting and analysing power consumption data of a general-purpose computer system, simulating common usage scenarios, in order to extract a power consumption profile for each scenario. Methods. We selected a desktop system running Windows XP as a test machine. Meanwhile, we developed 11 usage scenarios, classified by their functionality, and automated by a GUI testing tool. Then, we conducted several test runs of the scenarios, collecting power consumption data by means of a power meter. Results. Our analysis resulted in an estimation of a power consumption value for each scenario and software application used, obtaining that each single scenario introduced an overhead from 2 to 11 Watts, corresponding to an increase of about 12%. Conclusions. We determined that software and its usage patterns impacts consistently on the power consumption of computer systems. Further work will be devoted to evaluate how power consumption is affected by the usage of specific system resources, like processors, disks, memory et

The Green Lab: Experimentation in Software Energy Efficiency

Software energy efficiency is a research topic where experimentation is widely adopted. Nevertheless, current studies and research approaches struggle to find generalizable findings that can be used to build a consistent knowledge base for energy efficient software. To this end, we will discuss how to combine the traditional hypothesis-driven (top-down) approach with a bottom-up discovery approach. In this technical briefing, participants will learn the challenges that characterize the research in software energy efficiency. They will experience the complexity in this field and its implications for experimentatio

An Exploratory Empirical Assessment of Italian Open Government Data Quality With an eye to enabling linked open data

Context The diffusion of Linked Data and Open Data in recent years kept a very fast pace. However evidence from practitioners shows that disclosing data without proper quality control may jeopardize datasets reuse in terms of apps, linking, and other transformations. Objective Our goals are to understand practical problems experienced by open data users in using and integrating them and build a set of concrete metrics to assess the quality of disclosed data and better support the transition towards linked open data. Method We focus on Open Government Data (OGD), collecting problems experienced by developers and mapping them to a data quality model available in literature. Then we derived a set of metrics and applied them to evaluate a few samples of Italian OGD. Result We present empirical evidence concerning the common quality problems experienced by open data users when using and integrating datasets. The measurements effort showed a few acquired good practices and common weaknesses, and a set of discriminant factors among datasets. Conclusion The study represents the first empirical attempt to evaluate the quality of open datasets at an operational level. Our long-term goal is to support the transition towards Linked Open Government Data (LOGD) with a quality improvement process in the wake of the current practices in Software Qualit

In Quest for Proper Mediums for Technology Transfer in Software Engineering

Successful transfer of the results of research projects into practice is of great interest to all project participants. It can be assumed that different transfer mediums fulfill technology transfer (TT) with different levels of success and that they are impaired by different kinds of barriers. The goal of this study is to gain a better understanding about the different mediums used for TT in software engineering, and to identify barriers weakening the success of the application of such mediums. We conducted an exploratory study implemented by a survey in the context of a German research project with a broad range of used mediums. The main reported barriers were low expectations of usefulness, no awareness of existence, lack of resources, or inadequateness in terms of outdated material or being in an immature state. We interpreted our results as symptoms of a lack of a dissemination plan in the project. Further work will be needed to explore the implications for the transfer of research results (knowledge and techniques) to practice.Comment: Proceedings of the International Conference on Empirical Software Engineering and Measurement, 201

Increasing transparency through the open city toolkit

Degbelo, A., Granell, C., Trilles, S., Bhattacharya, D., & Wissing, J. (2020). Tell Me How My Open Data Is Re-used: Increasing Transparency Through the Open City Toolkit. In S. Hawken, H. Han, & C. Pettit (Eds.), Open Cities, Open Data: Collaborative Cities in the Information Era (pp. 311-330). [Chapter 14] Springer Singapore. https://doi.org/10.1007/978-981-13-6605-5_14The Open Data movement has been gaining momentum in recent years, with increasingly many public institutions making their data freely accessible. Despite much data being already open (and more to come), finding information about the actual usage of these open datasets is still a challenge. This chapter introduces two tools of the Open City Toolkit (OCT) that tackle this issue: a tool to increase transparency and interactive guidelines. Interviews with city council employees confirmed the utility of the transparency tool. Both tools can be used by city councils (for planning purposes) and by users interested to know more about the value of current open datasets (for information purposes).authorsversionpublishe

Naming the pain in requirements engineering : Contemporary problems, causes, and effects in practice

Requirements Engineering (RE) has received much attention in research and practice due to its importance to software project success. Its interdisciplinary nature, the dependency to the customer, and its inherent uncertainty still render the discipline difficult to investigate. This results in a lack of empirical data. These are necessary, however, to demonstrate which practically relevant RE problems exist and to what extent they matter. Motivated by this situation, we initiated the Naming the Pain in Requirements Engineering (NaPiRE) initiative which constitutes a globally distributed, bi-yearly replicated family of surveys on the status quo and problems in practical RE. In this article, we report on the qualitative analysis of data obtained from 228 companies working in 10 countries in various domains and we reveal which contemporary problems practitioners encounter. To this end, we analyse 21 problems derived from the literature with respect to their relevance and criticality in dependency to their context, and we complement this picture with a cause-effect analysis showing the causes and effects surrounding the most critical problems. Our results give us a better understanding of which problems exist and how they manifest themselves in practical environments. Thus, we provide a first step to ground contributions to RE on empirical observations which, until now, were dominated by conventional wisdom only.Peer reviewe

Understanding Green Software Development: A Conceptual Framework

The energy efficiency of IT has become one of the hottest topics in the last few years. The problem has been typically addressed by hardware manufacturers and designers, but recently the attention of industry and academia has shifted to the role of software for IT sustainability. Writing energy-efficient software is one of the most challenging issues in this area, because it requires not only a change of mindset for software developers and designers but also models and tools to measure and reduce the effect of software on the energy consumption of the underlying hardware. In this article, the authors present a conceptual framework that provides a unifying view of the strategies, models, and tools available so far for designing and developing greener softwar

Understanding Green Software Development: A Conceptual Framework

The energy efficiency of IT has become one of the hottest topics in the last few years. The problem has been typically addressed by hardware manufacturers and designers, but recently the attention of industry and academia has shifted to the role of software for IT sustainability. Writing energy-efficient software is one of the most challenging issues in this area, because it requires not only a change of mindset for software developers and designers but also models and tools to measure and reduce the effect of software on the energy consumption of the underlying hardware. In this article, the authors present a conceptual framework that provides a unifying view of the strategies, models, and tools available so far for designing and developing greener software

Ethical and Socially-Aware Data Labels

Many software systems today make use of large amount of personal data to make recommendations or decisions that affect our daily lives. These software systems generally operate without guarantees of non-discriminatory practices, as instead often required to human decision-makers, and therefore are attracting increasing scrutiny. Our research is focused on the specific problem of biased software-based decisions caused from biased input data. In this regard, we propose a data labeling framework based on the identification of measurable data characteristics that could lead to downstream discriminating effects. We test the proposed framework on a real dataset, which allowed us to detect risks of discrimination for the case of population groups