{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:OCDKOV3NN4NYOC6VGTC5MEJJJ3","short_pith_number":"pith:OCDKOV3N","canonical_record":{"source":{"id":"1910.05316","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2019-10-04T00:53:44Z","cross_cats_sorted":["cs.CV","cs.DC","cs.LG"],"title_canon_sha256":"e6c16d55e15ec9b1a01e7921689a88e770861f665c36e378f444a40b48cb41d0","abstract_canon_sha256":"29be7ea5b1ac775c023005691774ce894a6f41165d55d7fe5a7ddeee37622aa0"},"schema_version":"1.0"},"canonical_sha256":"7086a7576d6f1b870bd534c5d611294ed8cc722203d1bc9a0b4f00c6e56ceec7","source":{"kind":"arxiv","id":"1910.05316","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.05316","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"arxiv_version","alias_value":"1910.05316v1","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.05316","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_12","alias_value":"OCDKOV3NN4NY","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_16","alias_value":"OCDKOV3NN4NYOC6V","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_8","alias_value":"OCDKOV3N","created_at":"2026-07-05T00:11:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:OCDKOV3NN4NYOC6VGTC5MEJJJ3","target":"record","payload":{"canonical_record":{"source":{"id":"1910.05316","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2019-10-04T00:53:44Z","cross_cats_sorted":["cs.CV","cs.DC","cs.LG"],"title_canon_sha256":"e6c16d55e15ec9b1a01e7921689a88e770861f665c36e378f444a40b48cb41d0","abstract_canon_sha256":"29be7ea5b1ac775c023005691774ce894a6f41165d55d7fe5a7ddeee37622aa0"},"schema_version":"1.0"},"canonical_sha256":"7086a7576d6f1b870bd534c5d611294ed8cc722203d1bc9a0b4f00c6e56ceec7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:11:27.814800Z","signature_b64":"vWbz35ML3Nm8QBBOp4iZXjNtf2Y+XndMtIQo28OrVYRyHmQKsCym1FG8Z5Zp7b0ux4pcfFou/ef5tDfpt4eBCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7086a7576d6f1b870bd534c5d611294ed8cc722203d1bc9a0b4f00c6e56ceec7","last_reissued_at":"2026-07-05T00:11:27.814418Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:11:27.814418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.05316","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":"2026-07-05T00:11:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zv/wZueR88MPhgCxYzpnrMCYZyPhRsDcrbrOppe+YD/WMoQ0KJpdH0NGUpj2mRh1ZUeGEh5MFoPRxaUnJD/KBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:58:56.284317Z"},"content_sha256":"34a0e10b1a20e8f08b3ecfde7ed36ce73694296076f0ef667d204a5f2cc3a609","schema_version":"1.0","event_id":"sha256:34a0e10b1a20e8f08b3ecfde7ed36ce73694296076f0ef667d204a5f2cc3a609"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:OCDKOV3NN4NYOC6VGTC5MEJJJ3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.DC","cs.LG"],"primary_cat":"cs.NI","authors_text":"En Li, Liekang Zeng, Xu Chen, Zhi Zhou","submitted_at":"2019-10-04T00:53:44Z","abstract_excerpt":"As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep Neural Networks (DNNs) have quickly attracted widespread attention. However, it is challenging to run computation-intensive DNN-based tasks on mobile devices due to the limited computation resources. What's worse, traditional cloud-assisted DNN inference is heavily hindered by the significant wide-area network latency, leading to poor real-time performance as well as low quality of user experience. To address these challenges, in this paper, we propose Edgent, a framework that leverages edge computing for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.05316","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/1910.05316/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:11:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LrzB5jvArmS1JZGvyYRmD+6Pay/N6c2kIGhDlxgtey2oSx+3cUywi7VboZUavaQ6dQDf3JobQAF01CB5vrsADw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:58:56.284840Z"},"content_sha256":"f0cef109e80ef777f2539171db755ea14e52133b5ab7dbad8e3880f3968ec15e","schema_version":"1.0","event_id":"sha256:f0cef109e80ef777f2539171db755ea14e52133b5ab7dbad8e3880f3968ec15e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/bundle.json","state_url":"https://pith.science/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/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":"2026-08-06T09:58:56Z","links":{"resolver":"https://pith.science/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3","bundle":"https://pith.science/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/bundle.json","state":"https://pith.science/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OCDKOV3NN4NYOC6VGTC5MEJJJ3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:OCDKOV3NN4NYOC6VGTC5MEJJJ3","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":"29be7ea5b1ac775c023005691774ce894a6f41165d55d7fe5a7ddeee37622aa0","cross_cats_sorted":["cs.CV","cs.DC","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2019-10-04T00:53:44Z","title_canon_sha256":"e6c16d55e15ec9b1a01e7921689a88e770861f665c36e378f444a40b48cb41d0"},"schema_version":"1.0","source":{"id":"1910.05316","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.05316","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"arxiv_version","alias_value":"1910.05316v1","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.05316","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_12","alias_value":"OCDKOV3NN4NY","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_16","alias_value":"OCDKOV3NN4NYOC6V","created_at":"2026-07-05T00:11:27Z"},{"alias_kind":"pith_short_8","alias_value":"OCDKOV3N","created_at":"2026-07-05T00:11:27Z"}],"graph_snapshots":[{"event_id":"sha256:f0cef109e80ef777f2539171db755ea14e52133b5ab7dbad8e3880f3968ec15e","target":"graph","created_at":"2026-07-05T00:11:27Z","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/1910.05316/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep Neural Networks (DNNs) have quickly attracted widespread attention. However, it is challenging to run computation-intensive DNN-based tasks on mobile devices due to the limited computation resources. What's worse, traditional cloud-assisted DNN inference is heavily hindered by the significant wide-area network latency, leading to poor real-time performance as well as low quality of user experience. To address these challenges, in this paper, we propose Edgent, a framework that leverages edge computing for","authors_text":"En Li, Liekang Zeng, Xu Chen, Zhi Zhou","cross_cats":["cs.CV","cs.DC","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2019-10-04T00:53:44Z","title":"Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.05316","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":"sha256:34a0e10b1a20e8f08b3ecfde7ed36ce73694296076f0ef667d204a5f2cc3a609","target":"record","created_at":"2026-07-05T00:11:27Z","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":"29be7ea5b1ac775c023005691774ce894a6f41165d55d7fe5a7ddeee37622aa0","cross_cats_sorted":["cs.CV","cs.DC","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2019-10-04T00:53:44Z","title_canon_sha256":"e6c16d55e15ec9b1a01e7921689a88e770861f665c36e378f444a40b48cb41d0"},"schema_version":"1.0","source":{"id":"1910.05316","kind":"arxiv","version":1}},"canonical_sha256":"7086a7576d6f1b870bd534c5d611294ed8cc722203d1bc9a0b4f00c6e56ceec7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7086a7576d6f1b870bd534c5d611294ed8cc722203d1bc9a0b4f00c6e56ceec7","first_computed_at":"2026-07-05T00:11:27.814418Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:11:27.814418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vWbz35ML3Nm8QBBOp4iZXjNtf2Y+XndMtIQo28OrVYRyHmQKsCym1FG8Z5Zp7b0ux4pcfFou/ef5tDfpt4eBCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:11:27.814800Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.05316","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34a0e10b1a20e8f08b3ecfde7ed36ce73694296076f0ef667d204a5f2cc3a609","sha256:f0cef109e80ef777f2539171db755ea14e52133b5ab7dbad8e3880f3968ec15e"],"state_sha256":"7d271743835638952bc3f4b7551f5577063e3f86cab87481f860aa068fb89d17"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fSBQTM14Icp/0aWmsGWos3CQl/MVqNlaXZXQL6UCRpECUc5q03HNDFFbcLSAMLeR8PFZ+B8mLl/MylMOglVfAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T09:58:56.290740Z","bundle_sha256":"416e18019470d720c2896e5343a3b6c10dd83248eabff070f0f45ac688bf0b67"}}