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}
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.