{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:FW3CSO46XQE52KMOIAA35QVTCI","short_pith_number":"pith:FW3CSO46","schema_version":"1.0","canonical_sha256":"2db6293b9ebc09dd298e4001bec2b3120ebf434f30dd3c9ab93826a9f0e80a0e","source":{"kind":"arxiv","id":"1805.05674","version":1},"attestation_state":"computed","paper":{"title":"Approximate Edge Analytics for the IoT Ecosystem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Do Le Quoc, Myungjin Lee, Pramod Bhatotia, Ruichuan Chen, Zhenyu Wen","submitted_at":"2018-05-15T09:56:41Z","abstract_excerpt":"IoT-enabled devices continue to generate a massive amount of data. Transforming this continuously arriving raw data into timely insights is critical for many modern online services. For such settings, the traditional form of data analytics over the entire dataset would be prohibitively limiting and expensive for supporting real-time stream analytics. In this work, we make a case for approximate computing for data analytics in IoT settings. Approximate computing aims for efficient execution of workflows where an approximate output is sufficient instead of the exact output. The idea behind appro"},"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":"1805.05674","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-15T09:56:41Z","cross_cats_sorted":[],"title_canon_sha256":"9e9980c2b6d40680b7fbc88c5a857fae65bb1ab8454953a0482d18881c83a7b9","abstract_canon_sha256":"cb1cbf917181c90d9a9c88f473ef7d309e669ea1d95899883db041ac5098ed34"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:59.906898Z","signature_b64":"UGj/I8u0fPIMSl5r0NzPXpKUcciuEogRifI4T1bMQk/BkBEnUduXEruZMn1zeZ4EbOYLmdMREuKQtXxiy8QUCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2db6293b9ebc09dd298e4001bec2b3120ebf434f30dd3c9ab93826a9f0e80a0e","last_reissued_at":"2026-05-18T00:15:59.906499Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:59.906499Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Approximate Edge Analytics for the IoT Ecosystem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Do Le Quoc, Myungjin Lee, Pramod Bhatotia, Ruichuan Chen, Zhenyu Wen","submitted_at":"2018-05-15T09:56:41Z","abstract_excerpt":"IoT-enabled devices continue to generate a massive amount of data. Transforming this continuously arriving raw data into timely insights is critical for many modern online services. For such settings, the traditional form of data analytics over the entire dataset would be prohibitively limiting and expensive for supporting real-time stream analytics. In this work, we make a case for approximate computing for data analytics in IoT settings. Approximate computing aims for efficient execution of workflows where an approximate output is sufficient instead of the exact output. The idea behind appro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.05674","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":"1805.05674","created_at":"2026-05-18T00:15:59.906557+00:00"},{"alias_kind":"arxiv_version","alias_value":"1805.05674v1","created_at":"2026-05-18T00:15:59.906557+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.05674","created_at":"2026-05-18T00:15:59.906557+00:00"},{"alias_kind":"pith_short_12","alias_value":"FW3CSO46XQE5","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_16","alias_value":"FW3CSO46XQE52KMO","created_at":"2026-05-18T12:32:25.280505+00:00"},{"alias_kind":"pith_short_8","alias_value":"FW3CSO46","created_at":"2026-05-18T12:32:25.280505+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/FW3CSO46XQE52KMOIAA35QVTCI","json":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI.json","graph_json":"https://pith.science/api/pith-number/FW3CSO46XQE52KMOIAA35QVTCI/graph.json","events_json":"https://pith.science/api/pith-number/FW3CSO46XQE52KMOIAA35QVTCI/events.json","paper":"https://pith.science/paper/FW3CSO46"},"agent_actions":{"view_html":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI","download_json":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI.json","view_paper":"https://pith.science/paper/FW3CSO46","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1805.05674&json=true","fetch_graph":"https://pith.science/api/pith-number/FW3CSO46XQE52KMOIAA35QVTCI/graph.json","fetch_events":"https://pith.science/api/pith-number/FW3CSO46XQE52KMOIAA35QVTCI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI/action/storage_attestation","attest_author":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI/action/author_attestation","sign_citation":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI/action/citation_signature","submit_replication":"https://pith.science/pith/FW3CSO46XQE52KMOIAA35QVTCI/action/replication_record"}},"created_at":"2026-05-18T00:15:59.906557+00:00","updated_at":"2026-05-18T00:15:59.906557+00:00"}