M. Barkhordari and M. Niamanesh, ScaDiPaSi: An Effective Scalable and Distributable MapReduce-Based Method to Find Patient Similarity on Huge Healthcare Networks, Big Data Research, vol.2, issue.1, pp.19-27, 2015.
DOI : 10.1016/j.bdr.2015.02.004

K. H. Lee, Y. J. Lee, H. Choi, Y. D. Chung, and B. Moon, Parallel data processing with MapReduce, ACM SIGMOD Record, vol.40, issue.4, pp.11-20, 2012.
DOI : 10.1145/2094114.2094118

J. Dean and S. Ghemawat, MapReduce, Communications of the ACM, vol.51, issue.1, pp.107-113, 2008.
DOI : 10.1145/1327452.1327492

. Gi-cloud-initiative, Available in http://deity.gov.in/content/gi-cloud-initiative-meghraj, 2015.

L. Ding, J. Xin, G. Wang, and S. Huang, Commapreduce: An improvement of mapreduce with lightweight communication mechanisms, Database Systems for Advanced Applications, pp.150-168, 2012.

F. Highland and J. Stephenson, Fitting the Problem to the Paradigm: Algorithm Characteristics Required for Effective Use of MapReduce, Procedia Computer Science, vol.12, pp.212-217, 2012.
DOI : 10.1016/j.procs.2012.09.058

Y. Bu, B. Howe, M. Balazinska, and M. D. Ernst, HaLoop, Proceedings of the VLDB Endowment, pp.285-296, 2010.
DOI : 10.14778/1920841.1920881

V. S. Martha, W. Zhao, and X. Xu, h-MapReduce: A Framework for Workload Balancing in MapReduce, 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), pp.637-644, 2013.
DOI : 10.1109/AINA.2013.48

S. Groot, Modeling I/O Interference in Data Intensive Map-Reduce Applications, 2012 IEEE/IPSJ 12th International Symposium on Applications and the Internet, pp.206-209, 2012.
DOI : 10.1109/SAINT.2012.88

Y. Zhang, Q. Gao, L. Gao, and C. Wang, iMapReduce: A Distributed Computing Framework for Iterative Computation, Journal of Grid Computing, vol.10, issue.4, pp.47-68, 2012.
DOI : 10.1007/s10723-012-9204-9

B. Nicolae, D. Moise, G. Antoniu, L. Bougé, and M. Dorier, BlobSeer: Bringing high throughput under heavy concurrency to Hadoop Map-Reduce applications, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS), pp.1-11, 2010.
DOI : 10.1109/IPDPS.2010.5470433
URL : https://hal.archives-ouvertes.fr/inria-00456801

H. Mohamed and S. Marchand-maillet, MRO-MPI: MapReduce overlapping using MPI and an optimized data exchange policy, Parallel Computing, vol.39, issue.12, pp.851-866, 2013.
DOI : 10.1016/j.parco.2013.08.010

U. Srinivasan and B. Arunasalam, Leveraging Big Data Analytics to Reduce Healthcare Costs, IT Professional, vol.15, issue.6, pp.21-28, 2013.
DOI : 10.1109/MITP.2013.55

K. Jee and G. H. Kim, Potentiality of Big Data in the Medical Sector: Focus on How to Reshape the Healthcare System, Healthcare Informatics Research, vol.19, issue.2, pp.79-85, 2013.
DOI : 10.4258/hir.2013.19.2.79

O. Metaxas, H. Dimitropoulos, and Y. Ioannidis, AITION: A scalable KDD platform for Big Data Healthcare, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp.601-604, 2014.
DOI : 10.1109/BHI.2014.6864436