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US Patent 11917000 Message queue routing system

Patent 11917000 was granted and assigned to Bank of America on February, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Bank of America
Bank of America
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Current Assignee
Bank of America
Bank of America
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119170000
Patent Inventor Names
Anurajam Rajagopalan0
Sathyanarayana Rajendran0
Sunil Kumar Sriperambudur0
Date of Patent
February 27, 2024
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Patent Application Number
177428680
Date Filed
May 12, 2022
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Patent Citations
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US Patent 11237880 Dataflow all-reduce for reconfigurable processor systems
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US Patent 11418583 Transaction process management by dynamic transaction aggregation
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US Patent 11269678 Systems and methods for integrating third party services with a digital assistant
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US Patent 10200486 Mobile event notifications for network enabled objects
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US Patent 10356222 Reusable message flow between applications of a message broker integrated systems environment
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US Patent 10521284 System and method for management of deployed services and applications
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US Patent 10673936 Self-organized retail source request routing and distributed load sharing systems and methods
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US Patent 10778660 Managing multiple producer consumer—systems with non-identical idempotency keys
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Patent Primary Examiner
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Ario Etienne
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CPC Code
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G06F 9/5027
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H04L 45/302
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H04L 67/1008
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Patent abstract

A message queue routing system may be implemented into a message queue gateway to route data to Software component designed and deployed into MQ Gateway to route the data to the MQ cluster. A central processing unit (CPU) node analyzer reads real time health statistics of each of a plurality of MQ cluster processing nodes. Based the computation, the CPU node analyzer routes the message to a specified node of the cluster having a minimum of CPU load at that time. The CPU node analyzer analyzes information comprising at least CPU performance information and system idleness information. Each processing node enables dynamic message routing computations utilizing an artificial intelligence/machine learning framework and a plurality of trained predictive models. The predictive model is trained using a trained data set using text classification. Message information is extracted from the message via natural language processing and is processed via the trained model to identify characteristic information of the message. The characteristic information is used to select a subset of filters associated with message functionality. The message is routed to a target application based on filtering performed using the subset of filters.

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