{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:HKADBWDHHSWFCH7TOI4FCJR3J4","short_pith_number":"pith:HKADBWDH","schema_version":"1.0","canonical_sha256":"3a8030d8673cac511ff3723851263b4f0045d00aa38df8ecd6c13195db221c2e","source":{"kind":"arxiv","id":"2104.14050","version":1},"attestation_state":"computed","paper":{"title":"The Hidden cost of the Edge: A Performance Comparison of Edge and Cloud Latencies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.DC","authors_text":"Ahmed Ali-Eldin, Bin Wang, Prashant Shenoy","submitted_at":"2021-04-29T00:15:16Z","abstract_excerpt":"Edge computing has emerged as a popular paradigm for running latency-sensitive applications due to its ability to offer lower network latencies to end-users. In this paper, we argue that despite its lower network latency, the resource-constrained nature of the edge can result in higher end-to-end latency, especially at higher utilizations, when compared to cloud data centers. We study this edge performance inversion problem through an analytic comparison of edge and cloud latencies and analyze conditions under which the edge can yield worse performance than the cloud. To verify our analytic re"},"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":"2104.14050","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2021-04-29T00:15:16Z","cross_cats_sorted":["cs.PF"],"title_canon_sha256":"32d0d99e349f1780ef4ee307f0019e87aefda7ce734d086e7ba96c4d2d6a7043","abstract_canon_sha256":"dd59eec0a6ca7e7785ee943eb6449b6e0b642ec442a0096950f908bd5355c9a1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:36:12.463743Z","signature_b64":"26/tscvU24XASUVcb318W1nIYpTorh17iH5KP25CgiVn6OlZ0O0U4aLXoKdOcKtI5QYoPppyWdkqooy6xTh+Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a8030d8673cac511ff3723851263b4f0045d00aa38df8ecd6c13195db221c2e","last_reissued_at":"2026-07-05T02:36:12.463361Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:36:12.463361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Hidden cost of the Edge: A Performance Comparison of Edge and Cloud Latencies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.DC","authors_text":"Ahmed Ali-Eldin, Bin Wang, Prashant Shenoy","submitted_at":"2021-04-29T00:15:16Z","abstract_excerpt":"Edge computing has emerged as a popular paradigm for running latency-sensitive applications due to its ability to offer lower network latencies to end-users. In this paper, we argue that despite its lower network latency, the resource-constrained nature of the edge can result in higher end-to-end latency, especially at higher utilizations, when compared to cloud data centers. We study this edge performance inversion problem through an analytic comparison of edge and cloud latencies and analyze conditions under which the edge can yield worse performance than the cloud. To verify our analytic re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.14050","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/2104.14050/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":"2104.14050","created_at":"2026-07-05T02:36:12.463423+00:00"},{"alias_kind":"arxiv_version","alias_value":"2104.14050v1","created_at":"2026-07-05T02:36:12.463423+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.14050","created_at":"2026-07-05T02:36:12.463423+00:00"},{"alias_kind":"pith_short_12","alias_value":"HKADBWDHHSWF","created_at":"2026-07-05T02:36:12.463423+00:00"},{"alias_kind":"pith_short_16","alias_value":"HKADBWDHHSWFCH7T","created_at":"2026-07-05T02:36:12.463423+00:00"},{"alias_kind":"pith_short_8","alias_value":"HKADBWDH","created_at":"2026-07-05T02:36:12.463423+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.18725","citing_title":"Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions","ref_index":98,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4","json":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4.json","graph_json":"https://pith.science/api/pith-number/HKADBWDHHSWFCH7TOI4FCJR3J4/graph.json","events_json":"https://pith.science/api/pith-number/HKADBWDHHSWFCH7TOI4FCJR3J4/events.json","paper":"https://pith.science/paper/HKADBWDH"},"agent_actions":{"view_html":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4","download_json":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4.json","view_paper":"https://pith.science/paper/HKADBWDH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2104.14050&json=true","fetch_graph":"https://pith.science/api/pith-number/HKADBWDHHSWFCH7TOI4FCJR3J4/graph.json","fetch_events":"https://pith.science/api/pith-number/HKADBWDHHSWFCH7TOI4FCJR3J4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4/action/storage_attestation","attest_author":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4/action/author_attestation","sign_citation":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4/action/citation_signature","submit_replication":"https://pith.science/pith/HKADBWDHHSWFCH7TOI4FCJR3J4/action/replication_record"}},"created_at":"2026-07-05T02:36:12.463423+00:00","updated_at":"2026-07-05T02:36:12.463423+00:00"}