{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:FQ64RPP3RYNVRM5JMPR6AJKPLT","short_pith_number":"pith:FQ64RPP3","schema_version":"1.0","canonical_sha256":"2c3dc8bdfb8e1b58b3a963e3e0254f5ce87012ffe90126006d049c6021813935","source":{"kind":"arxiv","id":"2311.03853","version":1},"attestation_state":"computed","paper":{"title":"On Deep Reinforcement Learning for Traffic Steering Intelligent ORAN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Fatemeh Kavehmadavani, Symeon Chatzinotas, Thang X. Vu, Van-Dinh Nguyen","submitted_at":"2023-11-07T10:09:39Z","abstract_excerpt":"This paper aims to develop the intelligent traffic steering (TS) framework, which has recently been considered as one of the key developments of 3GPP for advanced 5G. Since achieving key performance indicators (KPIs) for heterogeneous services may not be possible in the monolithic architecture, a novel deep reinforcement learning (DRL)-based TS algorithm is proposed at the non-real-time (non-RT) RAN intelligent controller (RIC) within the open radio access network (ORAN) architecture. To enable ORAN's intelligence, we distribute traffic load onto appropriate paths, which helps efficiently allo"},"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":"2311.03853","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2023-11-07T10:09:39Z","cross_cats_sorted":[],"title_canon_sha256":"87de9241544ebebab2ceeeee55bce008de3c83133343a4734595ce94aa813449","abstract_canon_sha256":"34e3f2e571470d5bef5043c8b5383641c73cf89ded46bcd05c2a4509cfb8d257"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:10:06.818885Z","signature_b64":"Z1KQyrHopPEwT9i+YZKvyIAFUiyc16+lgYmZE5nTj3S0MZ93lzn6rxf3GipGIMvdJsH2SfG1F2iL7+nKm06tCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c3dc8bdfb8e1b58b3a963e3e0254f5ce87012ffe90126006d049c6021813935","last_reissued_at":"2026-07-05T07:10:06.818495Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:10:06.818495Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On Deep Reinforcement Learning for Traffic Steering Intelligent ORAN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Fatemeh Kavehmadavani, Symeon Chatzinotas, Thang X. Vu, Van-Dinh Nguyen","submitted_at":"2023-11-07T10:09:39Z","abstract_excerpt":"This paper aims to develop the intelligent traffic steering (TS) framework, which has recently been considered as one of the key developments of 3GPP for advanced 5G. Since achieving key performance indicators (KPIs) for heterogeneous services may not be possible in the monolithic architecture, a novel deep reinforcement learning (DRL)-based TS algorithm is proposed at the non-real-time (non-RT) RAN intelligent controller (RIC) within the open radio access network (ORAN) architecture. To enable ORAN's intelligence, we distribute traffic load onto appropriate paths, which helps efficiently allo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.03853","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.03853/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":"2311.03853","created_at":"2026-07-05T07:10:06.818547+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.03853v1","created_at":"2026-07-05T07:10:06.818547+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.03853","created_at":"2026-07-05T07:10:06.818547+00:00"},{"alias_kind":"pith_short_12","alias_value":"FQ64RPP3RYNV","created_at":"2026-07-05T07:10:06.818547+00:00"},{"alias_kind":"pith_short_16","alias_value":"FQ64RPP3RYNVRM5J","created_at":"2026-07-05T07:10:06.818547+00:00"},{"alias_kind":"pith_short_8","alias_value":"FQ64RPP3","created_at":"2026-07-05T07:10:06.818547+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/FQ64RPP3RYNVRM5JMPR6AJKPLT","json":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT.json","graph_json":"https://pith.science/api/pith-number/FQ64RPP3RYNVRM5JMPR6AJKPLT/graph.json","events_json":"https://pith.science/api/pith-number/FQ64RPP3RYNVRM5JMPR6AJKPLT/events.json","paper":"https://pith.science/paper/FQ64RPP3"},"agent_actions":{"view_html":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT","download_json":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT.json","view_paper":"https://pith.science/paper/FQ64RPP3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.03853&json=true","fetch_graph":"https://pith.science/api/pith-number/FQ64RPP3RYNVRM5JMPR6AJKPLT/graph.json","fetch_events":"https://pith.science/api/pith-number/FQ64RPP3RYNVRM5JMPR6AJKPLT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT/action/storage_attestation","attest_author":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT/action/author_attestation","sign_citation":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT/action/citation_signature","submit_replication":"https://pith.science/pith/FQ64RPP3RYNVRM5JMPR6AJKPLT/action/replication_record"}},"created_at":"2026-07-05T07:10:06.818547+00:00","updated_at":"2026-07-05T07:10:06.818547+00:00"}