A multiple task allocation framework for biological sequence comparison in a grid environment

The evolution of DNA sequencing techniques generated huge sequence repositories and hence the need for efficient algorithms to compare them. To increase search speed, heuristic algorithms like BLAST were developed and are widely used. In order to further reduce BLAST execution time, this paper evaluates an adaptive task allocation framework to perform BLAST searches in a grid environment against segmented genetic databases segments. Our results present very good speedups and also show that no single task allocation strategy is able to achieve the lowest execution times for all scenarios. Also, our results show that the proposed adaptive strategy was able to deal with the heterogeneous and non-dedicated nature of a grid