{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:UJZPL5BWSGOWEBAIPGBKAWFXAS","short_pith_number":"pith:UJZPL5BW","schema_version":"1.0","canonical_sha256":"a272f5f436919d6204087982a058b704b90ec4a9ecd561d84570d0b7d7103bd2","source":{"kind":"arxiv","id":"1902.03594","version":2},"attestation_state":"computed","paper":{"title":"Max-Min Fair Sensor Scheduling: Game-theoretic Perspective and Algorithmic Solution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Ling Shi, Shuang Wu, Xiaoqiang Ren, Yiguang Hong","submitted_at":"2019-02-10T13:18:04Z","abstract_excerpt":"We consider the design of a fair sensor schedule for a number of sensors monitoring different linear time-invariant processes. The largest average remote estimation error among all processes is to be minimized. We first consider a general setup for the max-min fair allocation problem. By reformulating the problem as its equivalent form, we transform the fair resource allocation problem into a zero-sum game between a \"judge\" and a resource allocator. We propose an equilibrium seeking procedure and show that there exists a unique Nash equilibrium in pure strategy for this game. We then apply the"},"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":"1902.03594","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2019-02-10T13:18:04Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"5538be3c02ea0b8843a04e555fe49ed9b3323965146a7ed93b16870e1a49f087","abstract_canon_sha256":"d73e585a7a0247752af3fb5e43731477f426054479f7b32d6bd4579aeccbac9b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T20:13:52.907163Z","signature_b64":"oqknrV+TEBL8rWPI808iA+ltZUeCLOhwIgrbaEx9Tfrztnh5rQOd+X4CGUN0XjR9L6mKAdX6JHlTKsMIMC3SCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a272f5f436919d6204087982a058b704b90ec4a9ecd561d84570d0b7d7103bd2","last_reissued_at":"2026-06-04T20:13:52.906662Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T20:13:52.906662Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Max-Min Fair Sensor Scheduling: Game-theoretic Perspective and Algorithmic Solution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Ling Shi, Shuang Wu, Xiaoqiang Ren, Yiguang Hong","submitted_at":"2019-02-10T13:18:04Z","abstract_excerpt":"We consider the design of a fair sensor schedule for a number of sensors monitoring different linear time-invariant processes. The largest average remote estimation error among all processes is to be minimized. We first consider a general setup for the max-min fair allocation problem. By reformulating the problem as its equivalent form, we transform the fair resource allocation problem into a zero-sum game between a \"judge\" and a resource allocator. We propose an equilibrium seeking procedure and show that there exists a unique Nash equilibrium in pure strategy for this game. We then apply the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.03594","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1902.03594/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"1902.03594","created_at":"2026-06-04T20:13:52.906741+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.03594v2","created_at":"2026-06-04T20:13:52.906741+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.03594","created_at":"2026-06-04T20:13:52.906741+00:00"},{"alias_kind":"pith_short_12","alias_value":"UJZPL5BWSGOW","created_at":"2026-06-04T20:13:52.906741+00:00"},{"alias_kind":"pith_short_16","alias_value":"UJZPL5BWSGOWEBAI","created_at":"2026-06-04T20:13:52.906741+00:00"},{"alias_kind":"pith_short_8","alias_value":"UJZPL5BW","created_at":"2026-06-04T20:13:52.906741+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/UJZPL5BWSGOWEBAIPGBKAWFXAS","json":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS.json","graph_json":"https://pith.science/api/pith-number/UJZPL5BWSGOWEBAIPGBKAWFXAS/graph.json","events_json":"https://pith.science/api/pith-number/UJZPL5BWSGOWEBAIPGBKAWFXAS/events.json","paper":"https://pith.science/paper/UJZPL5BW"},"agent_actions":{"view_html":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS","download_json":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS.json","view_paper":"https://pith.science/paper/UJZPL5BW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.03594&json=true","fetch_graph":"https://pith.science/api/pith-number/UJZPL5BWSGOWEBAIPGBKAWFXAS/graph.json","fetch_events":"https://pith.science/api/pith-number/UJZPL5BWSGOWEBAIPGBKAWFXAS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS/action/storage_attestation","attest_author":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS/action/author_attestation","sign_citation":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS/action/citation_signature","submit_replication":"https://pith.science/pith/UJZPL5BWSGOWEBAIPGBKAWFXAS/action/replication_record"}},"created_at":"2026-06-04T20:13:52.906741+00:00","updated_at":"2026-06-04T20:13:52.906741+00:00"}