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
地域：
NY
NY Armonk
摘要
A plurality of interfaces that share a plurality of resources in a storage controller are maintained. In response to an occurrence of a predetermined number of operations associated with an interface of the plurality of interfaces, an input is provided on a plurality of attributes of the storage controller to a machine learning module. In response to receiving the input, the machine learning module generates an output value corresponding to a number of resources of the plurality of resources to allocate to the interface in the storage controller.
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(9) Peak number of operations: Peak number of operations in the host adapter. [Shown via reference numeral 518];
(10) Average number of operations: Average number of operations in the host bus adapter. [Shown via reference numeral 520];
(11) Median number of operations: Median number of operations in the host bus adapter. [Shown via reference numeral 522];
(12) Number of high priority rejected: Number of high priority requests rejected from the host bus adapter. [Shown via reference numeral 524];
(13) Number of high priority active: Number of high priority requests active in the host bus adapter. [Shown via reference numeral 526];
(15) Number of host connections: How much connections from host to the host bus adapter (e.g. two connections vs 16 connections) [shown via reference numeral 528];
It should be noted that many other inputs that affect the selection of the best recovery mechanism may be included beyond those shown in
In certain embodiments the total number of TCBs are N (where N is a natural number), and the output 606 of the machine learning module 106 ranges from 0 to N indicating the number of TCBs to allocate to a port.
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