A flexible analysis and prediction framework on resource usage in public clouds

Chia Yu Lin, Yan Ann Chen, Yu Chee Tseng, Li Chun Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

2 引文 斯高帕斯(Scopus)

摘要

In cloud computing environments, users can rent virtual machines (VMs) from cloud providers to execute their programs or provide network services. While using this kind of cloud services, one of the biggest problems for the users is to determine the proper number of VMs to complete the jobs considering both budget and time. In this paper, we propose a resource prediction framework (RPF), which can help users choose the minimum number of virtual machines to complete their jobs within a user specified time constraint. In order to verify the feasibility of RPF, we have done three case studies, namely parallel frequent pattern growth (FP-Growth), parallel K-means, and Particle Swarm Optimization (PSO). FP-growth, K-means and PSO are data intensive algorithms. These algorithms are typically executed repeatedly with different execution parameters to find the optimal results. When evaluating RPF by these algorithms in cloud environments, we have to modify them to parallel versions. The evaluation results indicate that RPF can successfully obtain the minimum number of VMs with acceptable errors. According to our case studies, the proposed RPF can be adopted by data intensive jobs by providing flexibility to both end users and cloud system providers.

原文???core.languages.en_GB???
主出版物標題CloudCom 2012 - Proceedings
主出版物子標題2012 4th IEEE International Conference on Cloud Computing Technology and Science
頁面309-316
頁數8
DOIs
出版狀態已出版 - 2012
事件2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012 - Taipei, Taiwan
持續時間: 3 12月 20126 12月 2012

出版系列

名字CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science

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???event.eventtypes.event.conference???2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012
國家/地區Taiwan
城市Taipei
期間3/12/126/12/12

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