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Executing a biological sequence comparison application on a federated cloud environment

机译:在联合云环境中执行生物序列比较应用程序

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Smith-Waterman (SW) is a popular application in Bioinformatics which calculates the best score/alignment between two genomic sequences. Even though SW provides the best result, it is not widely used in genome projects due to huge requirements in computing power and memory space. Recently, Cloud Computing has been receiving a lot of attention since it is able to provide utility computing in an elastic environment. The advantages of Cloud Computing can be obtained at zero cost since many of the Public Clouds provide free usage slots, allowing users to run their applications for free in Cloud environments. Also, many Clouds can be put together and seen as a unique environment, creating Federated Clouds. In this paper, we propose and evaluate an approach to implement the SW algorithm in Federated Clouds. A hierarchical Multi-Cloud architecture is proposed which is able to transparently connect and manage several Clouds. The results obtained with our architecture and our MapReduce SW implementation in five Public Clouds show that, only by using the free quota, we were able to run the SW application over a huge genomic database in time that is comparable with the one obtained in multicore clusters, showing the appropriateness of our approach.
机译:Smith-Waterman(SW)是生物信息学中的一种流行应用程序,可计算两个基因组序列之间的最佳得分/比对。尽管SW提供了最佳结果,但由于对计算能力和存储空间的巨大要求,它并未广泛用于基因组项目中。近来,由于云计算能够在弹性环境中提供效用计算,因此备受关注。云计算的优势可以零成本获得,因为许多公共云都提供免费使用时段,从而允许用户在云环境中免费运行其应用程序。此外,许多云可以放在一起,并被视为一个独特的环境,从而创建联合云。在本文中,我们提出并评估了一种在联合云中实现SW算法的方法。提出了一种分层的多云架构,该架构能够透明地连接和管理多个云。使用我们的体系结构和五个公共云中的MapReduce SW实施获得的结果表明,只有使用免费配额,我们才能及时在庞大的基因组数据库上运行SW应用程序,这与多核集群中的数据库相当,显示出我们方法的适当性。

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