{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9703664","patent":{"patent_number":"US-9703664","title":"Self adaptive workload classification and forecasting in multi-tiered storage system using ARIMA time series modeling","assignee":null,"inventors":[],"filing_date":"2015-06-24T00:00:00.000Z","publication_date":"2017-07-11T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F","G06F","G06F"],"num_claims":16,"abstract":"Techniques are described data storage optimization that determine predicted values for I/O statistics using an ARIMA (auto-regressive integrated moving average) model. The ARIMA model may be used to capture periodic patterns and trends of workload I/O access to predict the future load demand. A current set of I/O statistics is collected for a current time period T. Using the current set and one or more ARIMA models, a predicted set of I/O statistics is determined for a next time period T+1. Each of the ARIMA models is characterized by model parameters including P denoting a number of auto-regressive terms, D denoting a number of nonseasonal difference needed for stationarity, and Q denoting a number of lagged forecast errors of prediction. A data storage optimizer may determine one or more data portions for movement from a current storage tier to a target storage tier using the predicted set of I/O statistics."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Self adaptive workload classification and forecasting in multi-tiered storage system using ARIMA time series modeling","description":"Techniques are described data storage optimization that determine predicted values for I/O statistics using an ARIMA (auto-regressive integrated moving average) model. The ARIMA model may be used to c","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9703664","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9703664","citation_suggestion":"Patentable. \"Self adaptive workload classification and forecasting in multi-tiered storage system using ARIMA time series modeling\" (US-9703664). https://patentable.app/patents/US-9703664","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9703664","json":"https://patentable.app/api/llm-context/US-9703664","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T05:35:21.090Z"}