Methods and devices for predictive diagnosis

A predictive, threading technique for reliability/availability analysis, response to error generation, error detection/correction, etc.

Active Publication Date: 2018-03-23
ORACLE INT CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These difficulties that plague the evolution of computer software may be due

Method used

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  • Methods and devices for predictive diagnosis
  • Methods and devices for predictive diagnosis
  • Methods and devices for predictive diagnosis

Examples

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Embodiment Construction

[0022] overview

[0023] Data can be categorized as fact, information, hypothesis, and directive. The activities of generating certain classes of data based on other classes of data by applying knowledge can be categorized as classification, assessment, resolution, and enactment. These categorization methods can be used to enhance the diagnostic system, such as through history keeping. Such diagnostic systems may include systems that predict computing system failures based on applying knowledge to system vital signs such as thread or stack segment strength and memory heap usage by virtual machines. These vital signs are facts that can be classified as generating information such as memory leaks, stuck threads, deadlocks, congestion, or other problems. Classification can include automatic generation of classes and trending of time series data with sampling intervals of irregular lengths.

[0024] Maintain relationships between data and activities

[0025]According to embodi...

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Abstract

Data can be categorized as facts, information, assumptions and instructions. Activities that generate certain categories of data based on other categories of data by applying knowledge can be categorized as classification, evaluation, interpretation, and implementation. Activities can be driven by a Classification-Assessment-Analysis-Actuation (CARE) control engine. CARE controls and these categorizations can be used to enhance numerous systems, such as diagnostic systems, such as through history keeping, machine learning and automation. Such diagnostic systems may include systems that predict computing system failures based on applying knowledge to system vital signs such as thread or stack segment strength and memory heap usage. These vital signs are facts that can be classified as generating information such as memory leaks, escort effects, or other problems. Classification can involve automatic generation of classes, states, observations, predictions, norms, objects, and processing of sampling intervals of irregular duration.

Description

[0001] priority [0002] This application also claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 61 / 811,106, filed April 11, 2013, and entitled "PREDICTIVE DIAGNOSIS OF SLA VIOLATIONS INCLOUD SERVICES BY SEASONAL TRENDING AND FORECASTING WITH FORECASTING WITH THREAD INTENSITYANALYTICS", the contents of which are incorporated herein by reference; and U.S. Patent Application No. 14 / 109578, filed December 17, 2013, entitled "PREDICTIVE DIAGNOSIS OF SLA VIOLATIONS IN CLOUD SERVICES BYSEASONAL TRENDING AND FORECASTING WITH THREAD INTENSITY ANALYTICS", the contents of which are incorporated herein by reference. This application also claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 61 / 811,102, filed April 11, 2013, and entitled "SEASONAL TRENDING, FORECASTING, ANOMALYDETECTION, AND ENDPOINT PREDICTION OF JAVA HEAP USAGE", the contents of which are incorporated herein by reference; and U.S. Patent Application No. 14 / 109...

Claims

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Application Information

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IPC IPC(8): G06F11/00G06F11/07
CPCG06F11/008G06F11/0715G06F11/0778G06F11/0718G06F11/0751G06F11/079G06F11/3003G06F11/3037G06F11/3409G06F11/3419G06F11/3452G06F11/3471G06F2201/865G06F2201/88G06F16/21G06F16/22G06F16/285G06F16/1824G06F9/4881G06F11/34H04L41/5009G06F9/45533
Inventor E·S·钱R·阿哈德A·戈内米A·C·圣托斯
Owner ORACLE INT CORP
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