{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:I7VW3OHMR7NHZVVSVONKB5YFFO","short_pith_number":"pith:I7VW3OHM","schema_version":"1.0","canonical_sha256":"47eb6db8ec8fda7cd6b2ab9aa0f7052bbb4237fc16efa3cd095c9d26521b056e","source":{"kind":"arxiv","id":"1106.4985","version":1},"attestation_state":"computed","paper":{"title":"Dynamic Fractional Resource Scheduling vs. Batch Scheduling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Fr\\'ed\\'eric Vivien (LIP, Henri Casanova (CoRG), INRIA Grenoble Rh\\^one-Alpes / LIP Laboratoire de l'Informatique du Parall\\'elisme), Mark Stillwell (LIP","submitted_at":"2011-06-24T14:54:51Z","abstract_excerpt":"We propose a novel job scheduling approach for homogeneous cluster computing platforms. Its key feature is the use of virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based scheduling approaches have focused primarily on technical issues or on extensions to existing batch scheduling systems, while we take a more aggressive approach and seek to find heuristics that maximize an objective metric correlated with job performance. We derive absolute performance bounds and develop algorithms for the online, non-clairvoyant version of our sched"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1106.4985","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2011-06-24T14:54:51Z","cross_cats_sorted":[],"title_canon_sha256":"24b7c8ed5e405f47a23b25e37dd363508ee2aa6f746c53b70938c26a1dba7684","abstract_canon_sha256":"9425137fa75c469f8e4d3088073fa3112fbec45ca730788a677a83b2f1153a43"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:19:22.620461Z","signature_b64":"l5duh6ChG8bzC7spwzyWNQOzeGwXlVI6+hl5uWX7iBLYy5lLGYKrk7MSKloAt8hFX9Mu/mWvUGFNp9IZDpkWCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47eb6db8ec8fda7cd6b2ab9aa0f7052bbb4237fc16efa3cd095c9d26521b056e","last_reissued_at":"2026-05-18T04:19:22.620061Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:19:22.620061Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamic Fractional Resource Scheduling vs. Batch Scheduling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Fr\\'ed\\'eric Vivien (LIP, Henri Casanova (CoRG), INRIA Grenoble Rh\\^one-Alpes / LIP Laboratoire de l'Informatique du Parall\\'elisme), Mark Stillwell (LIP","submitted_at":"2011-06-24T14:54:51Z","abstract_excerpt":"We propose a novel job scheduling approach for homogeneous cluster computing platforms. Its key feature is the use of virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based scheduling approaches have focused primarily on technical issues or on extensions to existing batch scheduling systems, while we take a more aggressive approach and seek to find heuristics that maximize an objective metric correlated with job performance. We derive absolute performance bounds and develop algorithms for the online, non-clairvoyant version of our sched"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1106.4985","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1106.4985","created_at":"2026-05-18T04:19:22.620120+00:00"},{"alias_kind":"arxiv_version","alias_value":"1106.4985v1","created_at":"2026-05-18T04:19:22.620120+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1106.4985","created_at":"2026-05-18T04:19:22.620120+00:00"},{"alias_kind":"pith_short_12","alias_value":"I7VW3OHMR7NH","created_at":"2026-05-18T12:26:30.835961+00:00"},{"alias_kind":"pith_short_16","alias_value":"I7VW3OHMR7NHZVVS","created_at":"2026-05-18T12:26:30.835961+00:00"},{"alias_kind":"pith_short_8","alias_value":"I7VW3OHM","created_at":"2026-05-18T12:26:30.835961+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO","json":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO.json","graph_json":"https://pith.science/api/pith-number/I7VW3OHMR7NHZVVSVONKB5YFFO/graph.json","events_json":"https://pith.science/api/pith-number/I7VW3OHMR7NHZVVSVONKB5YFFO/events.json","paper":"https://pith.science/paper/I7VW3OHM"},"agent_actions":{"view_html":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO","download_json":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO.json","view_paper":"https://pith.science/paper/I7VW3OHM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1106.4985&json=true","fetch_graph":"https://pith.science/api/pith-number/I7VW3OHMR7NHZVVSVONKB5YFFO/graph.json","fetch_events":"https://pith.science/api/pith-number/I7VW3OHMR7NHZVVSVONKB5YFFO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO/action/storage_attestation","attest_author":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO/action/author_attestation","sign_citation":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO/action/citation_signature","submit_replication":"https://pith.science/pith/I7VW3OHMR7NHZVVSVONKB5YFFO/action/replication_record"}},"created_at":"2026-05-18T04:19:22.620120+00:00","updated_at":"2026-05-18T04:19:22.620120+00:00"}