On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds
The cloud computing paradigm enables elastic resources to be scaled at run time satisfy customers’ demand. Cloud computing provisions on-demand service to users based on a pay-as-you-go manner. This novel paradigm enables cloud users or tenant users to afford computational resources in the form of v...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717718514 |
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| _version_ | 1849699246746370048 |
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| author | Wanbo Zheng Yuandou Wang Yunni Xia Quanwang Wu Lei Wu Kunyin Guo Weiling Li Xin Luo Qingsheng Zhu |
| author_facet | Wanbo Zheng Yuandou Wang Yunni Xia Quanwang Wu Lei Wu Kunyin Guo Weiling Li Xin Luo Qingsheng Zhu |
| author_sort | Wanbo Zheng |
| collection | DOAJ |
| description | The cloud computing paradigm enables elastic resources to be scaled at run time satisfy customers’ demand. Cloud computing provisions on-demand service to users based on a pay-as-you-go manner. This novel paradigm enables cloud users or tenant users to afford computational resources in the form of virtual machines as utilities, just like electricity, instead of paying for and building computing infrastructures by their own. Performance usually specified through service level agreement performance commitment of clouds is one of key research challenges and draws great research interests. Thus, performance issues of cloud infrastructures have been receiving considerable interest by both researchers and practitioners as a prominent activity for improving cloud quality. This work develops an analytical approach to dynamic performance modeling and trend prediction of fault-prone Infrastructure-as-a-Service clouds. The proposed analytical approach is based on a time-series and stochastic-process-based model. It is capable of predicting the expected system responsiveness and request rejection rate under variable load intensities, fault frequencies, multiplexing abilities, and instantiation processing times. A comparative study between theoretical and measured performance results through a real-world campus cloud is carried out to prove the correctness and accuracy of the proposed prediction approach. |
| format | Article |
| id | doaj-art-31d11cec71ab4d718ccea8aac22ae009 |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-31d11cec71ab4d718ccea8aac22ae0092025-08-20T03:18:39ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-07-011310.1177/1550147717718514On dynamic performance estimation of fault-prone Infrastructure-as-a-Service cloudsWanbo Zheng0Yuandou Wang1Yunni Xia2Quanwang Wu3Lei Wu4Kunyin Guo5Weiling Li6Xin Luo7Qingsheng Zhu8Chongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaChinese Academy of Sciences, Chongqing Institute of Green and Intelligent Technology, Chongqing, ChinaChongqing Key Laboratory of Software Theory and Technology, Chongqing University, Chongqing, ChinaThe cloud computing paradigm enables elastic resources to be scaled at run time satisfy customers’ demand. Cloud computing provisions on-demand service to users based on a pay-as-you-go manner. This novel paradigm enables cloud users or tenant users to afford computational resources in the form of virtual machines as utilities, just like electricity, instead of paying for and building computing infrastructures by their own. Performance usually specified through service level agreement performance commitment of clouds is one of key research challenges and draws great research interests. Thus, performance issues of cloud infrastructures have been receiving considerable interest by both researchers and practitioners as a prominent activity for improving cloud quality. This work develops an analytical approach to dynamic performance modeling and trend prediction of fault-prone Infrastructure-as-a-Service clouds. The proposed analytical approach is based on a time-series and stochastic-process-based model. It is capable of predicting the expected system responsiveness and request rejection rate under variable load intensities, fault frequencies, multiplexing abilities, and instantiation processing times. A comparative study between theoretical and measured performance results through a real-world campus cloud is carried out to prove the correctness and accuracy of the proposed prediction approach.https://doi.org/10.1177/1550147717718514 |
| spellingShingle | Wanbo Zheng Yuandou Wang Yunni Xia Quanwang Wu Lei Wu Kunyin Guo Weiling Li Xin Luo Qingsheng Zhu On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds International Journal of Distributed Sensor Networks |
| title | On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds |
| title_full | On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds |
| title_fullStr | On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds |
| title_full_unstemmed | On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds |
| title_short | On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds |
| title_sort | on dynamic performance estimation of fault prone infrastructure as a service clouds |
| url | https://doi.org/10.1177/1550147717718514 |
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