Determine a load balancing mechanism for allocation of shared resources in a storage system by training a machine learning module based on number of i/o operations

Abstract

A machine learning module receives inputs comprising attributes of a storage controller, wherein the attributes affect allocation of a plurality of resources to a plurality of interfaces. In response to a predetermined number of I/O operations occurring in the storage controller, a generation is made via forward propagation through a plurality of layers of the machine learning module, of an output value corresponding to a number of resources to allocate to an interface. A margin of error is calculated based on comparing the generated output value to an expected output value that is generated from an indication of a predetermined function based at least on a number of I/O operations that are waiting for a resource and a number of available resources. An adjustment is made of weights of links that interconnect nodes of the plurality of layers via back propagation, to reduce the margin of error.