Neural network-based load balancing in distributed storage systems
AssigneeRed Hat, Inc.
InventorsHarika Chebrolu, Sunil Angadi
Life of this patent
Estimating the term…
Abstract
A system, method, and computer readable medium train machine learning model using server parameters corresponding to a plurality of servers. The training produces an optimized feature set of the machine learning model. The system, method, and computer readable medium assign a server class to a received request based on the optimized feature set. The system, method, and computer readable medium compute, based on the optimized feature set, estimate response times for one or more servers from the plurality of servers corresponding to the server class. The system, method, and computer readable medium forward the request to one of the one or more servers based on the estimate response times.
Claims20
A method comprising:
- training a machine learning model using server parameters corresponding to a plurality of servers, wherein the training produces an optimized feature set of the machine learning model;
- responsive to receiving a request, assigning a server class to the request based on the optimized feature set;
- computing, by a processing device and based on the optimized feature set, estimate response times for one or more servers from the plurality of servers corresponding to the server class;
- and
- forwarding the request to one of the one or more servers based on the estimate response times.
A system comprising:
- a memory;
- and
- a processing device operatively coupled to the memory, the processing device to:
- train a machine learning model using server parameters corresponding to a plurality of servers, wherein the training produces an optimized feature set of the machine learning model;
- responsive to receiving a request, assign a server class to the request based on the optimized feature set;
- compute, based on the optimized feature set, estimate response times for one or more servers from the plurality of servers corresponding to the server class;
- and
- forward the request to one of the one or more servers based on the estimate response times.
A non-transitory computer readable medium, having instructions stored thereon which, when executed by a processing device, cause the processing device to:
- train a machine learning model using server parameters corresponding to a plurality of servers, wherein the training produces an optimized feature set of the machine learning model;
- responsive to receiving a request, assign a server class to the request based on the optimized feature set;
- compute, by the processing device and based on the optimized feature set, estimate response times for one or more servers from the plurality of servers corresponding to the server class;
- and
- forward the request to one of the one or more servers based on the estimate response times.
Dependencies are inferred from the claim text.