{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:RDWMI7SADYSVHYGZNNEU4YDF4O","short_pith_number":"pith:RDWMI7SA","schema_version":"1.0","canonical_sha256":"88ecc47e401e2553e0d96b494e6065e3a9135fa139e38a9b76ac4e1b9155343b","source":{"kind":"arxiv","id":"1402.2810","version":1},"attestation_state":"computed","paper":{"title":"Energy Efficient Scheduling of MapReduce Jobs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Dimitrios Letsios, Evripidis Bampis, Georgios Zois, Giorgio Lucarelli, Ioannis Milis, Vincent Chau","submitted_at":"2014-02-12T13:16:16Z","abstract_excerpt":"MapReduce is emerged as a prominent programming model for data-intensive computation. In this work, we study power-aware MapReduce scheduling in the speed scaling setting first introduced by Yao et al. [FOCS 1995]. We focus on the minimization of the total weighted completion time of a set of MapReduce jobs under a given budget of energy. Using a linear programming relaxation of our problem, we derive a polynomial time constant-factor approximation algorithm. We also propose a convex programming formulation that we combine with standard list scheduling policies, and we evaluate their performan"},"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":"1402.2810","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2014-02-12T13:16:16Z","cross_cats_sorted":[],"title_canon_sha256":"1f0a67b1c0d9e37a7fb7bd53974011262351c1006903116543936e1b37491217","abstract_canon_sha256":"57a2704abb89d28b8d2cbf4e3b4145133382145cca2fe8c8d28d5ac1292c2995"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:59:17.222249Z","signature_b64":"6l5PCP8vAS4OzCPQFmQNxZ8ymSnqYjMjsPjjSPOjgD3W/krsx4yEhWzV2Y8hp/5EGHLA+m73L1Ofry8i4Oa+BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88ecc47e401e2553e0d96b494e6065e3a9135fa139e38a9b76ac4e1b9155343b","last_reissued_at":"2026-05-18T02:59:17.221519Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:59:17.221519Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Energy Efficient Scheduling of MapReduce Jobs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Dimitrios Letsios, Evripidis Bampis, Georgios Zois, Giorgio Lucarelli, Ioannis Milis, Vincent Chau","submitted_at":"2014-02-12T13:16:16Z","abstract_excerpt":"MapReduce is emerged as a prominent programming model for data-intensive computation. In this work, we study power-aware MapReduce scheduling in the speed scaling setting first introduced by Yao et al. [FOCS 1995]. We focus on the minimization of the total weighted completion time of a set of MapReduce jobs under a given budget of energy. Using a linear programming relaxation of our problem, we derive a polynomial time constant-factor approximation algorithm. We also propose a convex programming formulation that we combine with standard list scheduling policies, and we evaluate their performan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1402.2810","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":"1402.2810","created_at":"2026-05-18T02:59:17.221641+00:00"},{"alias_kind":"arxiv_version","alias_value":"1402.2810v1","created_at":"2026-05-18T02:59:17.221641+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1402.2810","created_at":"2026-05-18T02:59:17.221641+00:00"},{"alias_kind":"pith_short_12","alias_value":"RDWMI7SADYSV","created_at":"2026-05-18T12:28:46.137349+00:00"},{"alias_kind":"pith_short_16","alias_value":"RDWMI7SADYSVHYGZ","created_at":"2026-05-18T12:28:46.137349+00:00"},{"alias_kind":"pith_short_8","alias_value":"RDWMI7SA","created_at":"2026-05-18T12:28:46.137349+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/RDWMI7SADYSVHYGZNNEU4YDF4O","json":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O.json","graph_json":"https://pith.science/api/pith-number/RDWMI7SADYSVHYGZNNEU4YDF4O/graph.json","events_json":"https://pith.science/api/pith-number/RDWMI7SADYSVHYGZNNEU4YDF4O/events.json","paper":"https://pith.science/paper/RDWMI7SA"},"agent_actions":{"view_html":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O","download_json":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O.json","view_paper":"https://pith.science/paper/RDWMI7SA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1402.2810&json=true","fetch_graph":"https://pith.science/api/pith-number/RDWMI7SADYSVHYGZNNEU4YDF4O/graph.json","fetch_events":"https://pith.science/api/pith-number/RDWMI7SADYSVHYGZNNEU4YDF4O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O/action/storage_attestation","attest_author":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O/action/author_attestation","sign_citation":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O/action/citation_signature","submit_replication":"https://pith.science/pith/RDWMI7SADYSVHYGZNNEU4YDF4O/action/replication_record"}},"created_at":"2026-05-18T02:59:17.221641+00:00","updated_at":"2026-05-18T02:59:17.221641+00:00"}