{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11989647","patent":{"patent_number":"US-11989647","title":"Self-learning scheduler for application orchestration on shared compute cluster","assignee":null,"inventors":[],"filing_date":"2019-02-08T00:00:00.000Z","publication_date":"2024-05-21T00:00:00.000Z","cpc_codes":["G06N","G06F","G06N","H04L","H04L"],"num_claims":17,"abstract":"The technology described herein is directed to a self-learning application scheduler for improved scheduling distribution of resource requests, e.g., job and service scheduling requests or tasks derived therefrom, initiated by applications on a shared compute infrastructure. More specifically, the self-learning application scheduler includes a reinforcement learning agent that iteratively learns a scheduling policy to improve scheduling distribution of the resource requests on the shared compute infrastructure. In some implementations, the reinforcement learning agent learns inherent characteristics and patterns of the resource requests initiated by the applications and orchestrates placement or scheduling of the resource requests on the shared compute infrastructure to minimize resource contention and thereby improve application performance for better overall user-experience."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Self-learning scheduler for application orchestration on shared compute cluster","description":"The technology described herein is directed to a self-learning application scheduler for improved scheduling distribution of resource requests, e.g., job and service scheduling requests or tasks deriv","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11989647","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-11989647","citation_suggestion":"Patentable. \"Self-learning scheduler for application orchestration on shared compute cluster\" (US-11989647). https://patentable.app/patents/US-11989647","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11989647","json":"https://patentable.app/api/llm-context/US-11989647","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T12:45:55.689Z"}