KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/55/55134/tde-22072020-153547/ |
Resumo: | Systems-of-Systems (SoS) have been playing an important role in the industry and academia as an answer to the ever growing complexity of software systems. This class of systems emerges from the interoperability of operational and managerial independent systems (called constituents) that work together to achieve more complex missions, not achievable by any of them individually. Constituents of an SoS generate at runtime a huge amount of data with high velocity and that is sometimes highly variable, characterizing a big data scenario. However, SoS have not taken advantages from the knowledge that could be discovered from such data, which could provide an overall understanding of the SoS behavior, support missions fulfillment, and enable the system to react to it. In this scenario, the main contribution of this Masters project is to provide means to support knowledge discovery in SoS, that is, to support the entire data cycle in SoS, from the collection in the constituents to the extraction of knowledge that will be useful for the system operation. For this, we propose KnowSoS, a Software Architecture for Knowledge Discovery in Systems-of-Systems, which assists in the design of a system that can be integrated into the SoS to control data flow and enable knowledge discovery. Besides that, we propose a set of guidelines that support SoS understanding and the development of the system designed by using KnowSoS. To evaluate this proposal, we present a proof of concept using the architecture and the guidelines to design and develop a knowledge discovery system in two different SoS domains, i.e., human resources and emergency management domain. As main results, the system improved the recommendation of job openings to candidates who are looking for a job in the human resources domain, and the precision of alerts for natural disasters to emergency stakeholders (i.e., police, hospitals, and firefighters) in the emergency management context. Such results indicate that, even as an initial approach, KnowSoS can be used to bring benefits in different domains where knowledge discovery is necessary to fulfill SoS missions. As future works, we intend to apply this approach in new domains and conduct more robust experimental studies. |
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KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-SystemsKnowSoS: Uma Arquitetura de Software para a Descoberta de Conhecimento em Sistemas-de-SistemasArquitetura de softwareDescoberta de conhecimentoKnoweldge discoverySistemas-de-SistemasSoftware architectureSystems-of-SystemsSystems-of-Systems (SoS) have been playing an important role in the industry and academia as an answer to the ever growing complexity of software systems. This class of systems emerges from the interoperability of operational and managerial independent systems (called constituents) that work together to achieve more complex missions, not achievable by any of them individually. Constituents of an SoS generate at runtime a huge amount of data with high velocity and that is sometimes highly variable, characterizing a big data scenario. However, SoS have not taken advantages from the knowledge that could be discovered from such data, which could provide an overall understanding of the SoS behavior, support missions fulfillment, and enable the system to react to it. In this scenario, the main contribution of this Masters project is to provide means to support knowledge discovery in SoS, that is, to support the entire data cycle in SoS, from the collection in the constituents to the extraction of knowledge that will be useful for the system operation. For this, we propose KnowSoS, a Software Architecture for Knowledge Discovery in Systems-of-Systems, which assists in the design of a system that can be integrated into the SoS to control data flow and enable knowledge discovery. Besides that, we propose a set of guidelines that support SoS understanding and the development of the system designed by using KnowSoS. To evaluate this proposal, we present a proof of concept using the architecture and the guidelines to design and develop a knowledge discovery system in two different SoS domains, i.e., human resources and emergency management domain. As main results, the system improved the recommendation of job openings to candidates who are looking for a job in the human resources domain, and the precision of alerts for natural disasters to emergency stakeholders (i.e., police, hospitals, and firefighters) in the emergency management context. Such results indicate that, even as an initial approach, KnowSoS can be used to bring benefits in different domains where knowledge discovery is necessary to fulfill SoS missions. As future works, we intend to apply this approach in new domains and conduct more robust experimental studies.Sistemas-de-Sistemas (do inglês, Systems-of-Systems, ou SoS) têm desempenhado um papel importante na indústria e na academia como resposta à crescente complexidade dos sistemas de software. Essa classe de sistemas emerge da interoperabilidade de sistemas que são operacionalmente e gerencialmente independentes (chamados de constituintes), e que trabalham juntos para alcançar missões complexas, impossíveis de serem alcançadas por qualquer um deles individualmente. Os constituintes de um SoS geram em tempo de execução uma enorme quantidade de dados com alta velocidade e, em muitas vezes, alta variabilidade, caracterizando um cenário de big data. No entanto, muitos desses sistemas não estão utilizando o conhecimento que poderia ser descoberto a partir desses dados, o que poderia fornecer uma compreensão geral do comportamento do SoS, apoiar na realização das missões, e permitir que o sistema reagisse a tal conhecimento. Nesse cenário, a principal contribuição deste projeto de mestrado é fornecer meios para apoiar a descoberta de conhecimento em SoS, isto é, apoiar o ciclo completo dos dados em SoS, desde a coleta dos dados nos constituintes até a extração de conhecimento que poderá ser util para a operação do sistema. Para isso, é proposta KnowSoS, uma Arquitetura de Software para Descoberta de Conhecimento em SoS, que auxilia no design de um sistema que será integrado no SoS para controle do fluxo de dados e a descoberta de conhecimento. Além disso, nós propormos um conjunto de guidelines the auxiliem no entendimento do SoS e no desenvolvimento do sistema construido por meio da KnowSoS. Para avaliar essa proposta, é apresentada uma prova de conceito usando a arquitetura e as guidelines para definir e desenvolver um sistema de descoberta de conhecimento em dois domínios diferentes, o domínio de recursos humanos e gerenciamento de emergências. Como principais resultados, o protótipo melhorou a recomendação de vagas para candidatos que procuram emprego no domínio de recursos humanos e a precisão de alertas de desastres naturais para as entidades interessadas em crises (ou seja, policiais, hospitais e bombeiros) no contexto de gerenciamento de emergências. Tais resultados indicam que, mesmo como uma abordagem inicial, KnowSoS pode ser usado para trazer benefícios em diferentes domínios em que a descoberta de conhecimento é necessária para cumprir as missões de SoS. Como trabalhos futuros, espera-se aplicar essa abordagem em novos domínios e realizar estudos experimentais mais robustos.Biblioteca Digitais de Teses e Dissertações da USPNakagawa, Elisa YumiSilva, Bruno Sena da2020-03-23info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/55/55134/tde-22072020-153547/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2020-08-13T00:45:33Zoai:teses.usp.br:tde-22072020-153547Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212020-08-13T00:45:33Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems KnowSoS: Uma Arquitetura de Software para a Descoberta de Conhecimento em Sistemas-de-Sistemas |
title |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
spellingShingle |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems Silva, Bruno Sena da Arquitetura de software Descoberta de conhecimento Knoweldge discovery Sistemas-de-Sistemas Software architecture Systems-of-Systems |
title_short |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
title_full |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
title_fullStr |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
title_full_unstemmed |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
title_sort |
KnowSoS: A Software Architecture for Knowledge Discovery in Systems-of-Systems |
author |
Silva, Bruno Sena da |
author_facet |
Silva, Bruno Sena da |
author_role |
author |
dc.contributor.none.fl_str_mv |
Nakagawa, Elisa Yumi |
dc.contributor.author.fl_str_mv |
Silva, Bruno Sena da |
dc.subject.por.fl_str_mv |
Arquitetura de software Descoberta de conhecimento Knoweldge discovery Sistemas-de-Sistemas Software architecture Systems-of-Systems |
topic |
Arquitetura de software Descoberta de conhecimento Knoweldge discovery Sistemas-de-Sistemas Software architecture Systems-of-Systems |
description |
Systems-of-Systems (SoS) have been playing an important role in the industry and academia as an answer to the ever growing complexity of software systems. This class of systems emerges from the interoperability of operational and managerial independent systems (called constituents) that work together to achieve more complex missions, not achievable by any of them individually. Constituents of an SoS generate at runtime a huge amount of data with high velocity and that is sometimes highly variable, characterizing a big data scenario. However, SoS have not taken advantages from the knowledge that could be discovered from such data, which could provide an overall understanding of the SoS behavior, support missions fulfillment, and enable the system to react to it. In this scenario, the main contribution of this Masters project is to provide means to support knowledge discovery in SoS, that is, to support the entire data cycle in SoS, from the collection in the constituents to the extraction of knowledge that will be useful for the system operation. For this, we propose KnowSoS, a Software Architecture for Knowledge Discovery in Systems-of-Systems, which assists in the design of a system that can be integrated into the SoS to control data flow and enable knowledge discovery. Besides that, we propose a set of guidelines that support SoS understanding and the development of the system designed by using KnowSoS. To evaluate this proposal, we present a proof of concept using the architecture and the guidelines to design and develop a knowledge discovery system in two different SoS domains, i.e., human resources and emergency management domain. As main results, the system improved the recommendation of job openings to candidates who are looking for a job in the human resources domain, and the precision of alerts for natural disasters to emergency stakeholders (i.e., police, hospitals, and firefighters) in the emergency management context. Such results indicate that, even as an initial approach, KnowSoS can be used to bring benefits in different domains where knowledge discovery is necessary to fulfill SoS missions. As future works, we intend to apply this approach in new domains and conduct more robust experimental studies. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-03-23 |
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.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/55/55134/tde-22072020-153547/ |
url |
https://www.teses.usp.br/teses/disponiveis/55/55134/tde-22072020-153547/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
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reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
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Universidade de São Paulo (USP) |
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USP |
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USP |
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Biblioteca Digital de Teses e Dissertações da USP |
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Biblioteca Digital de Teses e Dissertações da USP |
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Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
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