Towards a New Model of Storage and Access to Data in Big Data and Cloud Computing.

The technological revolution integrating multiple information sources and extension of computer science in different sectors led to the explosion of the data quantities, which reflects the scaling of volumes, numbers and types. These massive increases have resulted in the development of new location techniques and access to data. The final steps in this evolution have emerged new technologies: Cloud and Big Data. The reference implementation of the Clouds and Big Data storage is incontestably the Hadoop Distributed File System (HDFS). This latter is based on the separation of metadata to data that consists in the centralization and isolation of the metadata of storage servers. In this paper, the authors propose an approach to improve the service metadata for Hadoop to maintain consistency without much compromising performance and scalability of metadata by suggesting a mixed solution between centralization and distribution of metadata to enhance the performance and scalability of the model.