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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

專利號
US11175958B2
公開日期
2021-11-16
申請人
INTERNATIONAL BUSINESS MACHINES CORPORATION(US NY Armonk)
發(fā)明人
Lokesh M. Gupta; Matthew R. Craig; Beth Ann Peterson; Kevin John Ash
IPC分類
G06F9/50; G06N3/08; G06N20/00
技術(shù)領(lǐng)域
tcbs,learning,storage,in,machine,host,module,adapter,controller,resources
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.

說明書

In one example, management layer 64 may provide the functions described below. Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal provides access to the cloud computing environment for consumers and system administrators. Service level management provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

Workloads layer 66 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and load balancing via machine learning modules 68 as shown in FIGS. 1-19.

Additional Embodiment Details

權(quán)利要求

1
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