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 Title: |
US5745652:
Adaptive resource allocation using neural networks
[ Derwent Title ]
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| Country: |
US United States of America
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| Inventor: |
Bigus, Joseph Phillip; Rochester, MN
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| Assignee: |
International Business Machines Corporation, Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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| Published / Filed: |
1998-04-28
/ 1995-05-31
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| Application Number: |
US1995000455314
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| IPC Code: |
Advanced:
G06F 9/50;
Core:
G06F 9/46;
IPC-7:
G06E 1/00;
G06E 3/00;
G06F 15/18;
G06G 7/00;
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| ECLA Code: |
G06F9/50A2;
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| U.S. Class: |
Current:
706/014;
700/030;
700/032;
706/023;
706/025;
Original:
395/022;
395/021;
395/023;
364/150;
364/152;
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| Field of Search: |
395/022,20,21,24
364/149,150,151,152
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| Priority Number: |
| 1995-05-31 |
US1995000455314 |
| 1993-10-08 |
US1993000134953 |
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| Abstract: |
In a system comprising a plurality of resources for performing useful work, a resource allocation controller function, which is customized to the particular system's available resources and configuration, dynamically allocates resources and/or alters configuration to accommodate a changing workload. Preferably, the resource allocation controller is part of the computer's operating system which allocates resources of the computer system. The resource allocation controller uses a controller neural network for control, and a separate system model neural network for modelling the system and training the controller neural network. Performance data is collected by the system and used to train the system model neural network. A system administrator specifies computer system performance targets which indicate the desired performance of the system. Deviations in actual performance from desired performance are propagated back through the system model and ultimately to the controller neural network to create a closed loop system for resource allocation.
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| Attorney, Agent or Firm: |
Truelson, Roy W. ;
Gamon, Owen J. ;
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| Primary / Asst. Examiners: |
Hafiz, Tariq R.; Rhodes, Jason W.
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| Maintenance Status: |
E2 Expired Check current status
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| INPADOC Legal Status: |
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Family Legal Status Report
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| Parent Case: |
This is a divisional of application Ser. No. 08/134,953 filed on Oct. 8, 1993, now abandoned.
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| Family: |
Show 2 known family members
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First Claim:
Show all 13 claims |
What is claimed is:
1. A computer system, comprising:
- a plurality of resources for performing useful work on said computer system and capable of allocation by said system, wherein the useful work is divided into jobs, the jobs are categorized into a plurality of job classes, and the job classes require different amounts of the plurality of resources;
- means for receiving a set of performance objectives from a user, wherein said set of performance objectives represent desired performance of the plurality of job classes in said computer system;
- a resource allocation controller that allocates said resources within said computer system responsive to said performance objectives, said resource allocation controller having a plurality of adjustable parameters, wherein said resource controller changes allocation of said resources among the job classes based on said adjustable parameters being adjusted, wherein said resource allocation controller comprises a controller neural network having adjustable parameters, said neural network receiving said performance objectives as input and producing resource allocation information as output,
- a performance monitor for monitoring performance of said computer system to produce performance data representing actual performance of said computer system;
- comparison means for comparing said performance data produced by said performance monitor with said set of performance objectives to determine a difference between said objectives and said actual performance;
- feedback means coupled to said comparison means for adjusting said parameters in said resource allocation controller to reduce said difference between said objectives and said actual performance for each of the plurality of classes of work, wherein said feedback means comprises means for training said controller neural network, thereby adjusting said adjustable parameters, using said difference between said objectives and said actual performance.
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| Background / Summary: |
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| Drawing Descriptions: |
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| Description: |
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| Forward References: |
Show 48 U.S. patent(s) that reference this one
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