{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3EUIGRNG2YNRVJZXLBYVEXETL3","short_pith_number":"pith:3EUIGRNG","canonical_record":{"source":{"id":"1901.06476","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2019-01-19T07:09:22Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"03799d8d00f0c20a7b1c1ec1934b1f80eeaa8235dc5fbc8e4611fc49b15eb79f","abstract_canon_sha256":"d638d949a07c35ecafcfaa1e99d85e5191c0935399e4f43d8851bc3483094042"},"schema_version":"1.0"},"canonical_sha256":"d9288345a6d61b1aa7375871525c935ed06caf79be0d3af9c37063cb8999bc06","source":{"kind":"arxiv","id":"1901.06476","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.06476","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"arxiv_version","alias_value":"1901.06476v1","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.06476","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"pith_short_12","alias_value":"3EUIGRNG2YNR","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3EUIGRNG2YNRVJZX","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3EUIGRNG","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3EUIGRNG2YNRVJZXLBYVEXETL3","target":"record","payload":{"canonical_record":{"source":{"id":"1901.06476","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2019-01-19T07:09:22Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"03799d8d00f0c20a7b1c1ec1934b1f80eeaa8235dc5fbc8e4611fc49b15eb79f","abstract_canon_sha256":"d638d949a07c35ecafcfaa1e99d85e5191c0935399e4f43d8851bc3483094042"},"schema_version":"1.0"},"canonical_sha256":"d9288345a6d61b1aa7375871525c935ed06caf79be0d3af9c37063cb8999bc06","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:50.155706Z","signature_b64":"YhXudtZl+UoJI5fpuuAd+GNMUOH9DzYnss5YTRBaenJSkIp23ysyiM+fmQlJpchT+t3+cWidPbdx0TZsINoVBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d9288345a6d61b1aa7375871525c935ed06caf79be0d3af9c37063cb8999bc06","last_reissued_at":"2026-05-17T23:55:50.154867Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:50.154867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.06476","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:55:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jxcl03vhLFiXnAjsNvUT4W8K93VT+7FDpfmLfyEs+ShT1tMeLf8ioL0VelS1IcRIOQhBQRYS53F0SDhePPKJDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T12:25:39.842336Z"},"content_sha256":"d188ba82239bdc6b2a587255df9081bacad61200eb8378b54e123ed3f261ee3a","schema_version":"1.0","event_id":"sha256:d188ba82239bdc6b2a587255df9081bacad61200eb8378b54e123ed3f261ee3a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3EUIGRNG2YNRVJZXLBYVEXETL3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Learning Models for Content Popularity Prediction In Wireless Edge Caching","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"B. N. Bharath, Mathini Sellathurai, Navneet Garg, Tharmalingam Ratnarajah, Vimal Bhatia","submitted_at":"2019-01-19T07:09:22Z","abstract_excerpt":"Caching popular contents in advance is an important technique to achieve the low latency requirement and to reduce the backhaul costs in future wireless communications. Considering a network with base stations distributed as a Poisson point process (PPP), optimal content placement caching probabilities are derived for known popularity profile, which is unknown in practice. In this paper, online prediction (OP) and online learning (OL) methods are presented based on popularity prediction model (PPM) and Grassmannian prediction model (GPM), to predict the content profile for future time slots fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.06476","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:55:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"twg+9oFWxeWlRGkgZer4y+wYJHCXlMAxSMf2vXsXgZMpaB2Ms71C4t/S5CSyOIVn0/g4OTRDTpioZlVFo533Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T12:25:39.842983Z"},"content_sha256":"a91b01f6b3b578998cf6fcb3507d88239c46b2c406c6661076f4fb928a6a9a9a","schema_version":"1.0","event_id":"sha256:a91b01f6b3b578998cf6fcb3507d88239c46b2c406c6661076f4fb928a6a9a9a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/bundle.json","state_url":"https://pith.science/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-06T12:25:39Z","links":{"resolver":"https://pith.science/pith/3EUIGRNG2YNRVJZXLBYVEXETL3","bundle":"https://pith.science/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/bundle.json","state":"https://pith.science/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3EUIGRNG2YNRVJZXLBYVEXETL3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3EUIGRNG2YNRVJZXLBYVEXETL3","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":"d638d949a07c35ecafcfaa1e99d85e5191c0935399e4f43d8851bc3483094042","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2019-01-19T07:09:22Z","title_canon_sha256":"03799d8d00f0c20a7b1c1ec1934b1f80eeaa8235dc5fbc8e4611fc49b15eb79f"},"schema_version":"1.0","source":{"id":"1901.06476","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.06476","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"arxiv_version","alias_value":"1901.06476v1","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.06476","created_at":"2026-05-17T23:55:50Z"},{"alias_kind":"pith_short_12","alias_value":"3EUIGRNG2YNR","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3EUIGRNG2YNRVJZX","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3EUIGRNG","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:a91b01f6b3b578998cf6fcb3507d88239c46b2c406c6661076f4fb928a6a9a9a","target":"graph","created_at":"2026-05-17T23:55:50Z","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"},"paper":{"abstract_excerpt":"Caching popular contents in advance is an important technique to achieve the low latency requirement and to reduce the backhaul costs in future wireless communications. Considering a network with base stations distributed as a Poisson point process (PPP), optimal content placement caching probabilities are derived for known popularity profile, which is unknown in practice. In this paper, online prediction (OP) and online learning (OL) methods are presented based on popularity prediction model (PPM) and Grassmannian prediction model (GPM), to predict the content profile for future time slots fo","authors_text":"B. N. Bharath, Mathini Sellathurai, Navneet Garg, Tharmalingam Ratnarajah, Vimal Bhatia","cross_cats":["math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2019-01-19T07:09:22Z","title":"Online Learning Models for Content Popularity Prediction In Wireless Edge Caching"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.06476","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:d188ba82239bdc6b2a587255df9081bacad61200eb8378b54e123ed3f261ee3a","target":"record","created_at":"2026-05-17T23:55:50Z","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":"d638d949a07c35ecafcfaa1e99d85e5191c0935399e4f43d8851bc3483094042","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2019-01-19T07:09:22Z","title_canon_sha256":"03799d8d00f0c20a7b1c1ec1934b1f80eeaa8235dc5fbc8e4611fc49b15eb79f"},"schema_version":"1.0","source":{"id":"1901.06476","kind":"arxiv","version":1}},"canonical_sha256":"d9288345a6d61b1aa7375871525c935ed06caf79be0d3af9c37063cb8999bc06","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d9288345a6d61b1aa7375871525c935ed06caf79be0d3af9c37063cb8999bc06","first_computed_at":"2026-05-17T23:55:50.154867Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:55:50.154867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YhXudtZl+UoJI5fpuuAd+GNMUOH9DzYnss5YTRBaenJSkIp23ysyiM+fmQlJpchT+t3+cWidPbdx0TZsINoVBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:55:50.155706Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.06476","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d188ba82239bdc6b2a587255df9081bacad61200eb8378b54e123ed3f261ee3a","sha256:a91b01f6b3b578998cf6fcb3507d88239c46b2c406c6661076f4fb928a6a9a9a"],"state_sha256":"b06920f6e6bd4025b97c980267959e676c78de23675fea939f90eb37a3957c02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yTj7JOo+6rU3huVrI5YA1z/yNb9kjqutPuNYDM219a0/pf1WKla+3lJvOEk0T77f7ahIDAZqRsHS2iils3gLDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T12:25:39.847835Z","bundle_sha256":"c1831fa7b57eb576b5862c6299a8527a97d7a9b457c795d9ec6c1e673cdccf7a"}}