Leveraging Collection Diversity to Improve Energy Efficiency
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFPE |
dARK ID: | ark:/64986/0013000000xfs |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/35861 |
Resumo: | LIMA FILHO, Fernando José Castor de, também é conhecido em citações bibliográficas por: CASTOR FILHO, Fernando. |
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SANTOS, Renato Oliveira doshttp://lattes.cnpq.br/9079644368953375http://lattes.cnpq.br/7310046838140771LIMA FILHO, Fernando José Castor de2019-12-18T19:26:15Z2019-12-18T19:26:15Z2019-02-15SANTOS, Renato Oliveira dos. Leveraging Collection Diversity to Improve Energy Efficiency. 2019. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de Pernambuco, Recife, 2019.https://repositorio.ufpe.br/handle/123456789/35861ark:/64986/0013000000xfsLIMA FILHO, Fernando José Castor de, também é conhecido em citações bibliográficas por: CASTOR FILHO, Fernando.The increase in the use of pocket devices, such as smartphones and tablets, and the growth of embedded systems and data centers have moved the scientific community towards research lines involving the area of energy consumption. Many of these studies were initially focused on hardware, such as CPU and memory, and on operational systems, as means of improving the energy efficiency. This research, instead of focusing on these infrastructure components, proposes solutions to reduce the energy consumption of the applications that run on this infrastructure. In particular, this work proposes a tool called CT+, which statically analyses software systems that are written in Java and that use collections intensively, and proposes alternative collections implementations that are more efficient regarding energy consumption. The tool is an extension of another tool proposed in a previous work, called CECOTool, but it implements a series of improvements that solve limitations of the original approach. More specifically, depending on the context of use, it is capable of (i) recommending either collections that are safe for multiple threads or collections that are not (but that tend to be more efficient), (ii) do recommendations taking into account two other commonly used collections libraries, the Eclipse Collections and the Apache Commons Collections, (iii) distinguish operations executed on the beginning, middle or ending of a sequential structure; (iv) automatically apply the recommendations. Furthermore, CT+ makes use of points-to analysis to identify objects that are passed as parameters to other methods, making it possible for the recommendations to take into account the use of the same collection in different methods. In addition, besides being able to recommend to desktop or server applications, CT+ is also capable of recommending to mobile applications that target the Android platform. The CT+ evaluation shows how it was possible to improve the results of the original study by doing a comparison of the energy reduction on the two originally used benchmarks, reducing 5.49% of energy consumption against 3.49% on Xalan application and 4.83% against 4.37% on Tomcat. The effectiveness of CT+ in recommending collections for Android application was evaluated on the context of three different devices. It was possible to reach a reduction of energy consumption of up to 14.73%.A maior utilização de dispositivos de bolso, como smartphones e tablets, e o crescimento de sistemas embarcados e de data centers, têm levado a comunidade científica a iniciar linhas pesquisa na área de consumo de energia. Muitos desses estudos inicialmente tiveram foco em hardware, como CPU e memória RAM, e em sistemas operacionais, como forma de melhorar a eficiência energética. Este trabalho, ao invés de focar nestes componentes de infraestrutura, visa propor soluções para reduzir o consumo de energia das aplicações que rodam sobre essa infraestrutura. Em particular, propõe uma ferramenta chamada CT+, que analisa estaticamente sistemas de software escritos na linguagem Java e que usem coleções intensamente e propõe implementações alternativas de coleções que sejam mais eficientes do ponto de vista energético. A ferramenta é uma extensão de uma ferramenta proposta em um trabalho anterior, chamada CECOTool, mas implementa diversas melhorias que atacam limitações da abordagem original. Mais especificamente, dependendo do contexto de uso, ela é capaz de (i) recomendar tanto coleções seguras para múltiplas threads quanto coleções que não são seguras (mas que tendem a ser mais eficientes), (ii) fazer recomendações levando em conta mais duas bibliotecas de coleções muito usadas na prática, a Eclipse Collections e a Apache Commons Collections, (iii) distinguir operações realizadas no começo, no meio e no final de uma estrutura sequencial; (iv) aplicar automaticamente as recomendações realizadas. Além disso, CT+ utiliza-se de análise points-to para identificar objetos passados como parâmetros de métodos, o que torna possível que recomendações levem em conta usos de uma mesma coleção em diferentes métodos. Complementarmente, CT+ é capaz de realizar recomendações tanto para aplicações que rodam em máquinas desktop ou servidores quanto para aplicações móveis que tenham como alvo a plataforma Android. A avaliação de CT+ mostra como foi possível superar os resultados do estudo original fazendo um comparativo da melhoria de consumo de energia obtida nos dois benchmarks originalmente utilizados, economizando 5.49% de energia contra 3.49% na aplicação Xalan e 4.83% contra 4.37% no Tomcat. A eficácia de CT+ para recomendar melhorias para aplicações Android foi avaliada no contexto de três dispositivos diferentes. Foi possível obter uma redução de consumo de energia de até 14.73%.porUniversidade Federal de PernambucoPrograma de Pos Graduacao em Ciencia da ComputacaoUFPEBrasilAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessEngenharia de SoftwareCECOToolEnergy profilingLeveraging Collection Diversity to Improve Energy Efficiencyinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesismestradoreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPETEXTDISSERTAÇÃO Renato Oliveira dos Santos.pdf.txtDISSERTAÇÃO Renato Oliveira dos Santos.pdf.txtExtracted texttext/plain130676https://repositorio.ufpe.br/bitstream/123456789/35861/4/DISSERTA%c3%87%c3%83O%20Renato%20Oliveira%20dos%20Santos.pdf.txtc1f0109918a17a208f44f08d92b769acMD54THUMBNAILDISSERTAÇÃO Renato Oliveira dos Santos.pdf.jpgDISSERTAÇÃO Renato Oliveira dos Santos.pdf.jpgGenerated Thumbnailimage/jpeg1314https://repositorio.ufpe.br/bitstream/123456789/35861/5/DISSERTA%c3%87%c3%83O%20Renato%20Oliveira%20dos%20Santos.pdf.jpg852ccdc5b9375dab78f1d1706993267dMD55ORIGINALDISSERTAÇÃO Renato Oliveira dos Santos.pdfDISSERTAÇÃO Renato Oliveira dos Santos.pdfapplication/pdf1127101https://repositorio.ufpe.br/bitstream/123456789/35861/1/DISSERTA%c3%87%c3%83O%20Renato%20Oliveira%20dos%20Santos.pdfdc1ecd71f0a3ceae7e917b88e4cdd33fMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.pt_BR.fl_str_mv |
Leveraging Collection Diversity to Improve Energy Efficiency |
title |
Leveraging Collection Diversity to Improve Energy Efficiency |
spellingShingle |
Leveraging Collection Diversity to Improve Energy Efficiency SANTOS, Renato Oliveira dos Engenharia de Software CECOTool Energy profiling |
title_short |
Leveraging Collection Diversity to Improve Energy Efficiency |
title_full |
Leveraging Collection Diversity to Improve Energy Efficiency |
title_fullStr |
Leveraging Collection Diversity to Improve Energy Efficiency |
title_full_unstemmed |
Leveraging Collection Diversity to Improve Energy Efficiency |
title_sort |
Leveraging Collection Diversity to Improve Energy Efficiency |
author |
SANTOS, Renato Oliveira dos |
author_facet |
SANTOS, Renato Oliveira dos |
author_role |
author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/9079644368953375 |
dc.contributor.advisorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/7310046838140771 |
dc.contributor.author.fl_str_mv |
SANTOS, Renato Oliveira dos |
dc.contributor.advisor1.fl_str_mv |
LIMA FILHO, Fernando José Castor de |
contributor_str_mv |
LIMA FILHO, Fernando José Castor de |
dc.subject.por.fl_str_mv |
Engenharia de Software CECOTool Energy profiling |
topic |
Engenharia de Software CECOTool Energy profiling |
description |
LIMA FILHO, Fernando José Castor de, também é conhecido em citações bibliográficas por: CASTOR FILHO, Fernando. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-12-18T19:26:15Z |
dc.date.available.fl_str_mv |
2019-12-18T19:26:15Z |
dc.date.issued.fl_str_mv |
2019-02-15 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SANTOS, Renato Oliveira dos. Leveraging Collection Diversity to Improve Energy Efficiency. 2019. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de Pernambuco, Recife, 2019. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/35861 |
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ark:/64986/0013000000xfs |
identifier_str_mv |
SANTOS, Renato Oliveira dos. Leveraging Collection Diversity to Improve Energy Efficiency. 2019. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de Pernambuco, Recife, 2019. ark:/64986/0013000000xfs |
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https://repositorio.ufpe.br/handle/123456789/35861 |
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Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
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openAccess |
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Universidade Federal de Pernambuco |
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Programa de Pos Graduacao em Ciencia da Computacao |
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UFPE |
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