Cost evaluation of migrating a computation intensive problem from clusters to cloud

Abstract

Cloud has emerged as an alternative to clusters and grids. Its adoption as an execution environment capable of supporting the high requirements of scientific computations is still an open question. In a previous work, the authors conducted successfully a practical experience of taking advantage of clusters and grids to solve a semantic annotation problem in 178 days. In this work, the authors analyse the cost of solving that problem and compare it with the cost of solving it in a pure Cloud scenario. For this last, a detailed cost estimation is conducted according to the data extracted from the actual execution of a reduced dataset on Amazon EC2. As a result, the suitability of using Cloud-based solutions to solve large and complex scientific problems is discussed. © 2013 Springer International Publishing.