[go: up one dir, main page]

Jethuri et al., 2022 - Google Patents

Cognitive Metric Monitoring-Characterizing spatial-temporal behavior for anomaly detection

Jethuri et al., 2022

Document ID
10717431964084254968
Author
Jethuri K
Samudrala S
Priyadarshi P
Digitate M
Publication year
Publication venue
2022 IEEE International Conference on Big Data (Big Data)

External Links

Snippet

Organizations across the globe require a reliable anomaly detection solution that allows for continuous quality control. Considering the scale and complexity of infrastructure, the most common methods include setting a blanket threshold by using knowledge of the experts or …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0639Performance analysis
    • G06Q10/06393Score-carding, benchmarking or key performance indicator [KPI] analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0635Risk analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/34Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/008Reliability or availability analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2201/00Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/86Event-based monitoring
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/07Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202Market predictions or demand forecasting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Shi et al. Supply chain resilience assessment with financial considerations: A Bayesian network-based method
Ibidunmoye et al. Adaptive anomaly detection in performance metric streams
Kang et al. Real-time business process monitoring method for prediction of abnormal termination using KNNI-based LOF prediction
Kang et al. Periodic performance prediction for real‐time business process monitoring
Munirathinam et al. Big data predictive analtyics for proactive semiconductor equipment maintenance
US20220334904A1 (en) Automated Incident Detection and Root Cause Analysis
US20230064656A1 (en) Predictive maintenance of equipment
Cao et al. Load prediction for data centers based on database service
CN115237717A (en) Micro-service abnormity detection method and system
US20230214739A1 (en) Recommendation system for improving support for a service
Pai et al. Software effort estimation using a neural network ensemble
ur Rehman et al. User-side QoS forecasting and management of cloud services
Shah et al. Root cause detection using dynamic dependency graphs from time series data
Chakraborty et al. Building an automated and self-aware anomaly detection system
Dhanalaxmi et al. A review on software fault detection and prevention mechanism in software development activities
Chen et al. Balance: Bayesian linear attribution for root cause localization
Dienst et al. Integrated system for analyzing maintenance records in product improvement
Hasnain et al. Performance anomaly detection in web services: An rnn-based approach using dynamic quality of service features
Jethuri et al. Cognitive Metric Monitoring-Characterizing spatial-temporal behavior for anomaly detection
Bisht Convergence of AI and Observability: Predictive Insights Automation in Modern IT Operations
Tamanampudi AI-Enhanced Continuous Integration and Continuous Deployment Pipelines: Leveraging Machine Learning Models for Predictive Failure Detection, Automated Rollbacks, and Adaptive Deployment Strategies in Agile Software Development
US20240202093A1 (en) Methods and systems for generation and optimization of metric threshold for anomaly detection
Streiffer et al. Learning to simplify distributed systems management
Balasubramanian End-to-end model lifecycle management: An MLOPS framework for drift detection, root cause analysis, and continuous retraining
Gujral Survey: Anomaly detection methods