面向工业4.0的雾计算系统图分析

Nandor Verba, K. Chao, Anne E. James, J. Lewandowski, Xiang Fei, Chen-Fang Tsai
{"title":"面向工业4.0的雾计算系统图分析","authors":"Nandor Verba, K. Chao, Anne E. James, J. Lewandowski, Xiang Fei, Chen-Fang Tsai","doi":"10.1109/ICEBE.2017.17","DOIUrl":null,"url":null,"abstract":"Increased adoption of Fog Computing concepts into Cyber Physical Systems (CPS) is a driving force for implementing Industry 4.0. The modern industrial environment focuses on providing a flexible factory floor that suits the needs of modern manufacturing through the reduction of downtimes, reconfiguration times, adoption of new technologies and the increase of its production capabilities and rates. Fog Computing through CPS aims to provide a flexible orchestration and management platform that can meet the needs of this emerging industry model. Proposals on Fog Computing platform and Software Defined Networks (SDN) for Industry allow for resource virtualization and access throughout the system enabling large composite application systems to be deployed on multiple nodes. The increase of reliability, redundancy and runtime parameters as well as the reduction of costs in such systems are of key interest to Industry and researchers as well. The development of optimization algorithms and methods is made difficult by the complexity of such systems and the lack of real-world data on fog systems resulting in algorithms that are not being designed for real world scenarios. We propose a set of use-case scenarios based on our Industrial partner that we analyze to determine the graph based parameters of the system that allows us to scale and generate a more realistic testing scenario for future optimization attempts as well as determine the nature of such systems in comparison to other networks types. To show the differences between these scenarios and our real-world use-case we have selected a set of key graph characteristics based on which we analyze and compare the resulting graphs from the systems.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Graph Analysis of Fog Computing Systems for Industry 4.0\",\"authors\":\"Nandor Verba, K. Chao, Anne E. James, J. Lewandowski, Xiang Fei, Chen-Fang Tsai\",\"doi\":\"10.1109/ICEBE.2017.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Increased adoption of Fog Computing concepts into Cyber Physical Systems (CPS) is a driving force for implementing Industry 4.0. The modern industrial environment focuses on providing a flexible factory floor that suits the needs of modern manufacturing through the reduction of downtimes, reconfiguration times, adoption of new technologies and the increase of its production capabilities and rates. Fog Computing through CPS aims to provide a flexible orchestration and management platform that can meet the needs of this emerging industry model. Proposals on Fog Computing platform and Software Defined Networks (SDN) for Industry allow for resource virtualization and access throughout the system enabling large composite application systems to be deployed on multiple nodes. The increase of reliability, redundancy and runtime parameters as well as the reduction of costs in such systems are of key interest to Industry and researchers as well. The development of optimization algorithms and methods is made difficult by the complexity of such systems and the lack of real-world data on fog systems resulting in algorithms that are not being designed for real world scenarios. We propose a set of use-case scenarios based on our Industrial partner that we analyze to determine the graph based parameters of the system that allows us to scale and generate a more realistic testing scenario for future optimization attempts as well as determine the nature of such systems in comparison to other networks types. To show the differences between these scenarios and our real-world use-case we have selected a set of key graph characteristics based on which we analyze and compare the resulting graphs from the systems.\",\"PeriodicalId\":347774,\"journal\":{\"name\":\"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEBE.2017.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEBE.2017.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

在网络物理系统(CPS)中越来越多地采用雾计算概念是实现工业4.0的推动力。现代工业环境的重点是通过减少停机时间、重新配置时间、采用新技术以及提高生产能力和生产率,提供一个灵活的工厂车间,以满足现代制造业的需求。通过CPS的雾计算旨在提供一个灵活的编排和管理平台,以满足这种新兴行业模式的需求。雾计算平台和工业软件定义网络(SDN)的建议允许在整个系统中进行资源虚拟化和访问,从而使大型复合应用系统能够部署在多个节点上。这些系统的可靠性、冗余度和运行参数的提高以及成本的降低都是工业界和研究人员感兴趣的关键问题。由于此类系统的复杂性以及缺乏雾系统的真实数据,导致算法不是针对真实世界场景设计的,因此优化算法和方法的开发变得困难。我们提出了一组基于我们的工业合作伙伴的用例场景,我们对其进行分析,以确定系统的基于图形的参数,使我们能够扩展并为未来的优化尝试生成更现实的测试场景,并确定与其他网络类型相比,此类系统的性质。为了显示这些场景和我们的真实用例之间的差异,我们选择了一组关键图形特征,我们基于这些特征分析和比较来自系统的结果图形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Graph Analysis of Fog Computing Systems for Industry 4.0
Increased adoption of Fog Computing concepts into Cyber Physical Systems (CPS) is a driving force for implementing Industry 4.0. The modern industrial environment focuses on providing a flexible factory floor that suits the needs of modern manufacturing through the reduction of downtimes, reconfiguration times, adoption of new technologies and the increase of its production capabilities and rates. Fog Computing through CPS aims to provide a flexible orchestration and management platform that can meet the needs of this emerging industry model. Proposals on Fog Computing platform and Software Defined Networks (SDN) for Industry allow for resource virtualization and access throughout the system enabling large composite application systems to be deployed on multiple nodes. The increase of reliability, redundancy and runtime parameters as well as the reduction of costs in such systems are of key interest to Industry and researchers as well. The development of optimization algorithms and methods is made difficult by the complexity of such systems and the lack of real-world data on fog systems resulting in algorithms that are not being designed for real world scenarios. We propose a set of use-case scenarios based on our Industrial partner that we analyze to determine the graph based parameters of the system that allows us to scale and generate a more realistic testing scenario for future optimization attempts as well as determine the nature of such systems in comparison to other networks types. To show the differences between these scenarios and our real-world use-case we have selected a set of key graph characteristics based on which we analyze and compare the resulting graphs from the systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Integrated System Optimization Based on the Boiler Combustion and Denitration with Denitration Operating Cost Consideration Chinese Questions Classification in the Law Domain Dust Removal with Boundary and Spatial Constraint for Videos Captured in Car Indexing for Large Scale Data Querying Based on Spark SQL Finding K-Most Influential Users in Social Networks for Information Diffusion Based on Network Structure and Different User Behavioral Patterns
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1