Determine a load balancing mechanism for allocation of shared resources in a storage system using a machine learning module based on number of I/O operations
摘要
說明書
The neural network 302 may comprise a collection of nodes with links connecting them, where the links are referred to as connections. For example,
The connection between one node and another is represented by a number called a weight, where the weight may be either positive (if one node excites another) or negative (if one node suppresses or inhibits another). Training the neural network 302 entails calibrating the weights in the neural network 302 via mechanisms referred to as forward propagation 316 and back propagation 322. Bias nodes that are not connected to any previous layer may also be maintained in the neural network 302. A bias is an extra input of 1 with a weight attached to it for a node.
