{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KNBR3RJTHDR2VJNEIJAWJRES7V","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c8872b06bc18364c3541594186ea74e6fd1d2979dc06252ee960d46ed137314f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2025-08-11T21:27:40Z","title_canon_sha256":"156189c9633a58fff5d71dc520a85b0287c9f15d7013293dd5aacd8c1610eaed"},"schema_version":"1.0","source":{"id":"2508.08479","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.08479","created_at":"2026-07-05T11:52:29Z"},{"alias_kind":"arxiv_version","alias_value":"2508.08479v1","created_at":"2026-07-05T11:52:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.08479","created_at":"2026-07-05T11:52:29Z"},{"alias_kind":"pith_short_12","alias_value":"KNBR3RJTHDR2","created_at":"2026-07-05T11:52:29Z"},{"alias_kind":"pith_short_16","alias_value":"KNBR3RJTHDR2VJNE","created_at":"2026-07-05T11:52:29Z"},{"alias_kind":"pith_short_8","alias_value":"KNBR3RJT","created_at":"2026-07-05T11:52:29Z"}],"graph_snapshots":[{"event_id":"sha256:af97bb0bd303349d0fdded00ce4c9bc24853f314d8861a7b38c20eb70ed5e7c3","target":"graph","created_at":"2026-07-05T11:52:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2508.08479/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate and adaptive network throughput prediction is essential for latency-sensitive and bandwidth-intensive applications in 5G and emerging 6G networks. However, most existing methods rely on centralized training with uniformly collected data, limiting their applicability in heterogeneous mobile environments with non-IID data distributions. This paper presents the first comprehensive benchmarking of federated learning (FL) strategies for throughput prediction in realistic 5G edge scenarios. We evaluate three aggregation algorithms - FedAvg, FedProx, and FedBN - across four time-series archi","authors_text":"Basabdatta Palit, Sandip Chakraborty, Soumyajit Chatterjee, Yuvraj Dutta","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2025-08-11T21:27:40Z","title":"Benchmarking Federated Learning for Throughput Prediction in 5G Live Streaming Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.08479","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:525697e0b64f1c134360982c536c20d524c872cd60c1c697ad15b17fc75ff353","target":"record","created_at":"2026-07-05T11:52:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c8872b06bc18364c3541594186ea74e6fd1d2979dc06252ee960d46ed137314f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2025-08-11T21:27:40Z","title_canon_sha256":"156189c9633a58fff5d71dc520a85b0287c9f15d7013293dd5aacd8c1610eaed"},"schema_version":"1.0","source":{"id":"2508.08479","kind":"arxiv","version":1}},"canonical_sha256":"53431dc53338e3aaa5a4424164c492fd7413303cd6ecfec13f4f507be5636d1e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53431dc53338e3aaa5a4424164c492fd7413303cd6ecfec13f4f507be5636d1e","first_computed_at":"2026-07-05T11:52:29.148829Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:52:29.148829Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UnEt+0WNgbIW+/Pq/mYLG1Bbsp9umt1gXfvaqV/N3RI3E4Pl9vLgZprrfNOq7VEXQajYLFAqIctoyW0/CASFCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:52:29.149282Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.08479","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:525697e0b64f1c134360982c536c20d524c872cd60c1c697ad15b17fc75ff353","sha256:af97bb0bd303349d0fdded00ce4c9bc24853f314d8861a7b38c20eb70ed5e7c3"],"state_sha256":"4ae08fc8a0e2af8564db54163494d481662ce2576c7d320b8ca06e044c3a17bc"}