Towards Service-Oriented Enterprise Architectures for Big Data Applications in the Cloud

A. Zimmermann, M. Pretz, G. Zimmermann, D. Firesmith, Ilia Petrov
{"title":"Towards Service-Oriented Enterprise Architectures for Big Data Applications in the Cloud","authors":"A. Zimmermann, M. Pretz, G. Zimmermann, D. Firesmith, Ilia Petrov","doi":"10.1109/EDOCW.2013.21","DOIUrl":null,"url":null,"abstract":"Applications with Service-oriented Enterprise Architectures in the Cloud are emerging and will shape future trends in technology and communication. The development of such applications integrates Enterprise Architecture and Management with Architectures for Services & Cloud Computing, Web Services, Semantics and Knowledge-based Systems, Big Data Management, among other Architecture Frameworks and Software Engineering Methods. In the present work in progress research, we explore Service-oriented Enterprise Architectures and application systems in the context of Big Data applications in cloud settings. Using a Big Data scenario, we investigate the integration of Services and Cloud Computing architectures with new capabilities of Enterprise Architectures and Management. The underlying architecture reference model can be used to support semantic analysis and program comprehension of service-oriented Big Data Applications. Enterprise Services Computing is the current trend for powerful large-scale information systems, which increasingly converge with Cloud Computing environments. In this paper we combine architectures for services with cloud computing. We propose a new integration model for service-oriented Enterprise Architectures on basis of ESARC - Enterprise Services Architecture Reference Cube, which is our previous developed service-oriented enterprise architecture classification framework, with MFESA - Method Framework for Engineering System Architectures - for the design of service-oriented enterprise architectures, and the systematic development, diagnostics and optimization of architecture artifacts of service-oriented cloud-based enterprise systems for Big Data applications.","PeriodicalId":376599,"journal":{"name":"2013 17th IEEE International Enterprise Distributed Object Computing Conference Workshops","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 17th IEEE International Enterprise Distributed Object Computing Conference Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDOCW.2013.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 48

Abstract

Applications with Service-oriented Enterprise Architectures in the Cloud are emerging and will shape future trends in technology and communication. The development of such applications integrates Enterprise Architecture and Management with Architectures for Services & Cloud Computing, Web Services, Semantics and Knowledge-based Systems, Big Data Management, among other Architecture Frameworks and Software Engineering Methods. In the present work in progress research, we explore Service-oriented Enterprise Architectures and application systems in the context of Big Data applications in cloud settings. Using a Big Data scenario, we investigate the integration of Services and Cloud Computing architectures with new capabilities of Enterprise Architectures and Management. The underlying architecture reference model can be used to support semantic analysis and program comprehension of service-oriented Big Data Applications. Enterprise Services Computing is the current trend for powerful large-scale information systems, which increasingly converge with Cloud Computing environments. In this paper we combine architectures for services with cloud computing. We propose a new integration model for service-oriented Enterprise Architectures on basis of ESARC - Enterprise Services Architecture Reference Cube, which is our previous developed service-oriented enterprise architecture classification framework, with MFESA - Method Framework for Engineering System Architectures - for the design of service-oriented enterprise architectures, and the systematic development, diagnostics and optimization of architecture artifacts of service-oriented cloud-based enterprise systems for Big Data applications.
面向云中的大数据应用的面向服务的企业架构
云中具有面向服务的企业架构的应用程序正在兴起,并将塑造技术和通信的未来趋势。这些应用程序的开发将企业架构和管理与服务和云计算架构、Web服务、语义和基于知识的系统、大数据管理以及其他架构框架和软件工程方法集成在一起。在目前正在进行的研究工作中,我们探索了云环境下大数据应用背景下的面向服务的企业架构和应用系统。使用大数据场景,我们研究了服务和云计算架构与企业架构和管理的新功能的集成。底层架构参考模型可用于支持面向服务的大数据应用的语义分析和程序理解。企业服务计算是当前强大的大型信息系统的发展趋势,它与云计算环境日益融合。在本文中,我们将服务架构与云计算结合起来。基于ESARC(企业服务体系结构参考数据集)和MFESA(工程系统体系结构方法框架)提出了面向服务的企业体系结构集成模型,该模型是我们之前开发的面向服务的企业体系结构分类框架,用于面向服务的企业体系结构设计和系统开发。面向服务的云企业系统大数据应用体系结构构件的诊断与优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信