US 12,229,166 B2
Self-organization of data storage
Harinath Meedinti Bhaskara Reddy, Charlotte, NC (US); Manu Kurian, Dallas, TX (US); Jayachandra Varma, Irvington, TX (US); Erica Perkins, Charlotte, NC (US); and Aeric Solow, Richardson, TX (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jun. 5, 2023, as Appl. No. 18/205,646.
Prior Publication US 2024/0403326 A1, Dec. 5, 2024
Int. Cl. G06F 16/28 (2019.01)
CPC G06F 16/285 (2019.01) 18 Claims
OG exemplary drawing
 
1. A method of tuning data storage within a data mesh based on machine learning outputs, said method using a processor, said method comprising the steps of:
associating in a first relational database, a metadata tag with:
a classifying feature; and
a first storage instruction;
identifying an initial storage location for an incoming dataset within the data mesh, the identifying being tunable using a machine learning system, the machine learning system executing on the processor, the tunability comprising:
upon receipt of said incoming dataset by said data mesh, ascertaining whether said incoming dataset comprises said classifying feature;
upon confirmation that the incoming dataset comprises said classifying feature, using the processor to:
obtain said metadata tag and said first storage instruction from said first relational database;
annotate said incoming dataset with said metadata tag, thereby generating a tagged dataset;
store said tagged dataset in the initial storage location, according to said first storage instruction; and
associate, in a second relational database, said metadata tag with said initial storage location;
subsequently modifying the first storage instruction using the machine learning system, the modifying comprising using the machine learning system to:
identify a previously stored dataset that is possibly a closest match to the incoming dataset;
determine a degree of match between the previously stored dataset and the incoming dataset based on a set of predetermined parameters;
derive storage rules from a storage instruction corresponding to the previously stored dataset in response to determining that the degree of match is the closest match; and
generate a modified storage instruction using the storage rules, the modified storage instruction comprising an instruction to store the incoming dataset in a second storage location that differs from the initial storage location;
connecting the initial storage location to the second storage location via a data link, the data link comprising a transmitter, a receiver and a data telecommunication circuit, the data link being governed by a link protocol; and
upon generation of said modified storage instruction, transferring, via the data link, said incoming dataset from the initial storage location to the second storage location.