Abstract: 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.
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