{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:UN5273AL7YKWILJBCRLEZOXXDH","short_pith_number":"pith:UN5273AL","schema_version":"1.0","canonical_sha256":"a37bafec0bfe15642d2114564cbaf719cab62972c2b05e6b763f008be95f0223","source":{"kind":"arxiv","id":"1610.07419","version":1},"attestation_state":"computed","paper":{"title":"Using Machine Learning to Detect Noisy Neighbors in 5G Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NI","authors_text":"Alberto Mozo, Bruno Ordozgoiti, Danny Raz, Elisha Rosensweig, Itai Segall, Udi Margolin","submitted_at":"2016-10-24T14:07:56Z","abstract_excerpt":"5G networks are expected to be more dynamic and chaotic in their structure than current networks. With the advent of Network Function Virtualization (NFV), Network Functions (NF) will no longer be tightly coupled with the hardware they are running on, which poses new challenges in network management. Noisy neighbor is a term commonly used to describe situations in NFV infrastructure where an application experiences degradation in performance due to the fact that some of the resources it needs are occupied by other applications in the same cloud node. These situations cannot be easily identifie"},"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":"1610.07419","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2016-10-24T14:07:56Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9c297b0f217a83875a8bd1e899c675cf379cba3a6f1f1b13a3adaf4dab523ac1","abstract_canon_sha256":"6b34991c54a5616cafa0c3d496d1c1e632ce746a0fff1ac545f012ed3c3f5f41"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:01:30.137013Z","signature_b64":"bss3w4e/w06xaJAKXU0fHwyMr87+FoIUQzzdchZ671kp8U5AbTYad+7FZzJwG915ouFsYrpfN7WyCinYCm8PAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a37bafec0bfe15642d2114564cbaf719cab62972c2b05e6b763f008be95f0223","last_reissued_at":"2026-05-18T01:01:30.136577Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:01:30.136577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Using Machine Learning to Detect Noisy Neighbors in 5G Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NI","authors_text":"Alberto Mozo, Bruno Ordozgoiti, Danny Raz, Elisha Rosensweig, Itai Segall, Udi Margolin","submitted_at":"2016-10-24T14:07:56Z","abstract_excerpt":"5G networks are expected to be more dynamic and chaotic in their structure than current networks. With the advent of Network Function Virtualization (NFV), Network Functions (NF) will no longer be tightly coupled with the hardware they are running on, which poses new challenges in network management. Noisy neighbor is a term commonly used to describe situations in NFV infrastructure where an application experiences degradation in performance due to the fact that some of the resources it needs are occupied by other applications in the same cloud node. These situations cannot be easily identifie"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.07419","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":"1610.07419","created_at":"2026-05-18T01:01:30.136641+00:00"},{"alias_kind":"arxiv_version","alias_value":"1610.07419v1","created_at":"2026-05-18T01:01:30.136641+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.07419","created_at":"2026-05-18T01:01:30.136641+00:00"},{"alias_kind":"pith_short_12","alias_value":"UN5273AL7YKW","created_at":"2026-05-18T12:30:46.583412+00:00"},{"alias_kind":"pith_short_16","alias_value":"UN5273AL7YKWILJB","created_at":"2026-05-18T12:30:46.583412+00:00"},{"alias_kind":"pith_short_8","alias_value":"UN5273AL","created_at":"2026-05-18T12:30:46.583412+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/UN5273AL7YKWILJBCRLEZOXXDH","json":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH.json","graph_json":"https://pith.science/api/pith-number/UN5273AL7YKWILJBCRLEZOXXDH/graph.json","events_json":"https://pith.science/api/pith-number/UN5273AL7YKWILJBCRLEZOXXDH/events.json","paper":"https://pith.science/paper/UN5273AL"},"agent_actions":{"view_html":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH","download_json":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH.json","view_paper":"https://pith.science/paper/UN5273AL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1610.07419&json=true","fetch_graph":"https://pith.science/api/pith-number/UN5273AL7YKWILJBCRLEZOXXDH/graph.json","fetch_events":"https://pith.science/api/pith-number/UN5273AL7YKWILJBCRLEZOXXDH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH/action/storage_attestation","attest_author":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH/action/author_attestation","sign_citation":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH/action/citation_signature","submit_replication":"https://pith.science/pith/UN5273AL7YKWILJBCRLEZOXXDH/action/replication_record"}},"created_at":"2026-05-18T01:01:30.136641+00:00","updated_at":"2026-05-18T01:01:30.136641+00:00"}