• gowri

Due to advances in high-throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches that process collected data into new knowledge in a timely manner. In this work proposed an effective technique for reducing the resource problems in clouds using the enhanced map reducing algorithm. The map reduce algorithm generates a solution which is further optimized with the help of optimization algorithm. It shows an effectual topology for solving the resource model for resource problem solution. Deployment of optimization algorithm opted for multi objective problem is Modified Artificial Bee Colony Algorithm (MABC) which delivered best optimized result and less computation time is utilized to unfurl the determined objective, upshots of the proposition topology has depicted promising and effectual results and minimized computational exertion. In this proposed method, the execution time is reduced largely when compared to the existing method.

Keywords: Modified Artificial Bee Colony Algorithm (MABC), enhanced map reducing algorithm

"LARGE BIOLOGICAL DATASET ANALYSIS USING ENHANCED MAP REDUCING METHOD WITH MODIFIED ARTIFICIAL BEE COLONY OPTIMIZATION (MABC)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.68-82, December-2018, Available :http://www.jetir.org/papers/JETIR1812811.pdf

"LARGE BIOLOGICAL DATASET ANALYSIS USING ENHANCED MAP REDUCING METHOD WITH MODIFIED ARTIFICIAL BEE COLONY OPTIMIZATION (MABC)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp68-82, December-2018, Available at : http://www.jetir.org/papers/JETIR1812811.pdf