Resultados de búsqueda para Energy Efficiency

The development of environmentally friendly software is not a trivial project. And, in order to determine how efficient software is from an energy point of view, it is essential to be able to evaluate the energy consumed when it is running. However, simply having measuring instruments that allow us to fully analyse consumption may not in itself be enough. To ensure that the results obtained are correct and appropriate it is imperative to follow the correct steps. This paper presents the support for the activities and roles required to analyze the energy efficiency of the software. A process has thus been developed to guide researchers in carrying out the software+IBk-s energy consumption measurements, from study design to analysis and reporting of results. This process is known as the Green Software Measurement Process (GSMP) and it ensures greater control over the measurements made, improving the reliability, consistency, and coherence of the measurements. It also ensures that the results obtained are comparable with other studies and facilitates the replicability of the analyses performed. To define the GSMP, we have followed the method engineering approach and we also have taken as our basis well-known approaches to software measurement and good practices related to green software that have been proposed by other authors. To support the systematic development, management and growth of our proposed process by using a standardized representation, we have chosen to use SPEM 2.0+ADs this has also allowed us to generate documentation in a standard format that is available to anyone who wants to consult it on the web. This contribution, we believe, helps software professionals to be aware that there are processes and tools to evaluate the energy efficiency of the software applications they develop. They can thus develop software that is environmentally friendly.

Databases are a key part of any Information System (IS), as they are concerned with storing and retrieving the data required by the system. Among the different types of databases, the relational ones are the most widely used. According to previous works, there are two measures that affect the complexity of relational databases, the number of foreign keys (NFK) and the depth of the referential tree (DRT). However, a new kid on the block has appeared in the last years, the energy consumption of software in general and, therefore, also in databases. Bearing this in mind, the aim of this paper is to determine whether the results about the complexity of relational databases are related to the energy consumption of the database. To do that we have measured the energy consumption required by four different relational database schemas, each one of them representing different values for NFK and DRT. Moreover, we have implemented and used the four schemas on four different database management systems. As a result, we can conclude that both measures have a noticeable impact not only on the complexity but also in the consumption of the database when querying.

The impact of energy consumption on the environment andthe economy is raising awareness of «green»software engineering. HADASis an eco-assistant that makes developers aware of the influence oftheir designs and implementations on the energy consumption and performanceof the final product. In this paper, we extend HADAS to bettersupport the requirements of users: researchers, automatically dumpingthe energy-consumption of different software solutions; and developers,who want to perform a sustainability analysis of different software solutions.This analysis has been extended by adding Pearson’s chi-squareddifferentials and Bootstrapping statistics, to automatically check the significanceof correlations of the energy consumption, or the execution time,with any other variable (e.g., the number of users) that can influencethe selection of a particular eco-efficient configuration. We have evaluatedour approach by performing a sustainability analysis of the mostcommon web servers (i.e. PHP servers) using the time and energy datameasured with the Watts Up? Pro tool previously dumped in HADAS.We show how HADAS helps web server providers to make a trade-offbetween energy consumption and execution time, allowing them to selldifferent server configurations with different costs without modifying thehardware.

Context: Quality attributes play a critical role in the architecture elicitation phase. Software Sustainability and energy efficiency is becoming a critical quality attribute that can be used as a selection criteria to choose from among different design or implementation alternatives. Energy efficiency usually competes with other non-functional requirements, like for instance, performance.Objective: This paper presents a process that helps developers to automatically generate optimum configurations of functional quality attributes in terms of energy efficiency and performance. Functional quality attributes refer to the behavioral properties that need to be incorporated inside a software architecture to fulfill a particular quality attribute (e.g., encryption and authentication for the security quality attribute, logging for the usability quality attribute).Method: Quality attributes are characterized to identify their design and implementation variants and how the different configurations influence both energy efficiency and performance. A usage model for each characterized quality attribute is defined. The variability of quality attributes, as well as the energy efficiency and performance experiment results, are represented as a constraint satisfaction problem with the goal of formally reasoning about it. Then, a configuration of the selected functional quality attributes is automatically generated, which is optimum with respect to a selected objective function.Results: Software developers can improve the energy efficiency and/or performance of their applications by using our approach to perform a richer analysis of the energy consumption and performance of different alternatives for functional quality attributes. We show quantitative values of the benefits of using our approach and discuss the threats to validity.Conclusions: The process presented in this paper will help software developers to build more energy efficient software, whilst also being aware of how their decisions affect other quality attributes, such as performance.