DEVELOPING AN ACCURATE DISPERSED STORAGE NETWORK MEMORY PERFORMANCE MODEL THROUGH TRAINING
A computing device includes an interface configured to interface and communicate with a dispersed or distributed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable w...
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description | A computing device includes an interface configured to interface and communicate with a dispersed or distributed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. The computing device receives first samples corresponding to inputs that characterize configuration of the DSN and receives second samples corresponding to outputs that characterize system behavior of the DSN. The computing device then processes the first and samples to generate a DSN model to generate predictive performance of the outputs based on various values of the inputs. In some instances, the DSN model is based on a neural network model that employs the inputs that characterize the configuration of the DSN and generates the outputs that characterize system behavior of the DSN. |
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The computing device receives first samples corresponding to inputs that characterize configuration of the DSN and receives second samples corresponding to outputs that characterize system behavior of the DSN. The computing device then processes the first and samples to generate a DSN model to generate predictive performance of the outputs based on various values of the inputs. In some instances, the DSN model is based on a neural network model that employs the inputs that characterize the configuration of the DSN and generates the outputs that characterize system behavior of the DSN.</description><language>eng</language><subject>BASIC ELECTRONIC CIRCUITRY ; CALCULATING ; CODE CONVERSION IN GENERAL ; CODING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; DECODING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20181025&DB=EPODOC&CC=US&NR=2018307561A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20181025&DB=EPODOC&CC=US&NR=2018307561A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Iljazi, Ilir</creatorcontrib><title>DEVELOPING AN ACCURATE DISPERSED STORAGE NETWORK MEMORY PERFORMANCE MODEL THROUGH TRAINING</title><description>A computing device includes an interface configured to interface and communicate with a dispersed or distributed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. The computing device receives first samples corresponding to inputs that characterize configuration of the DSN and receives second samples corresponding to outputs that characterize system behavior of the DSN. The computing device then processes the first and samples to generate a DSN model to generate predictive performance of the outputs based on various values of the inputs. 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subjects | BASIC ELECTRONIC CIRCUITRY CALCULATING CODE CONVERSION IN GENERAL CODING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES DECODING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
title | DEVELOPING AN ACCURATE DISPERSED STORAGE NETWORK MEMORY PERFORMANCE MODEL THROUGH TRAINING |
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