Intelligent Software Defined Storage

The Big Data situation requires a qualitatively different type of information processing. This problem brings in a new type of a computational model that explicitly works only with a relatively small portion of the available data, while the rest of the data just implicitly affects selection of the given working portion. The unavoidable restrictions on the operations with overabundant data translate into the design of the brain in accordance with the fundamental Freud´s idea of unconsciousness. This design is contemplated in our paper. To implement such kind of Big Data processing facilities in practice we introduce a particular construction of Software Defined Storage. This construction emulates the basic features of the suggested memory organization of the brain: multi-attribute cortical map, content-addressable access, and stream resolution of multiple responses. The envisioned Software Defined Storage incorporates two developments: memory device for multiatribute items that can be accessed by any combinations of attributes using Fuzzyfind procedures and massive distributed streaming for resolution of multiple responses.