{"id":"https://openalex.org/W7164903891","doi":"https://doi.org/10.48550/arxiv.2606.15199","title":"CogGuard: Cognitive and Operational Profiling for Proactive Warning in Edge Intelligent Services","display_name":"CogGuard: Cognitive and Operational Profiling for Proactive Warning in Edge Intelligent Services","publication_year":2026,"publication_date":"2026-06-13","ids":{"openalex":"https://openalex.org/W7164903891","doi":"https://doi.org/10.48550/arxiv.2606.15199"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.15199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.15199","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138749101","display_name":"Zhi Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Zhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137682382","display_name":"Weihao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Weihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138721969","display_name":"Zhiqing Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Zhiqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138704106","display_name":"Hanshuai Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Hanshuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109597339","display_name":"Q L","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Qianli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138738919","display_name":"Weijia Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Weijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5016584164","display_name":"Weidong Zhao","orcid":"https://orcid.org/0000-0003-4144-7303"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9307000041007996,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9307000041007996,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.009100000374019146,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.004800000227987766,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.6920999884605408},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.5174000263214111},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.40149998664855957},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.38679999113082886},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.3765999972820282},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.36910000443458557},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.35589998960494995},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.335999995470047}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8210999965667725},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.6920999884605408},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.5174000263214111},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.40149998664855957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39010000228881836},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3693000078201294},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35260000824928284},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.33410000801086426},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3237999975681305},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C49020025","wikidata":"https://www.wikidata.org/wiki/Q1059099","display_name":"Chaining","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2547000050544739},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.15199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.15199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.47548654675483704,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Proactive":[0],"warning":[1,149,227],"is":[2],"an":[3,20],"important":[4],"capability":[5],"for":[6,55,68,116],"edge":[7,69,92,117],"intelligent":[8,118],"services,":[9],"where":[10],"the":[11,100,230,242],"system":[12],"predicts":[13],"whether":[14],"a":[15,79,113,135,179],"subject":[16],"will":[17],"successfully":[18],"complete":[19],"incoming":[21],"task":[22,152],"under":[23],"strict":[24],"latency":[25],"and":[26,37,77,85,140,150,197,211,222],"privacy":[27],"constraints.":[28],"Such":[29],"prediction":[30,133,236],"depends":[31],"on":[32,90,191,195,225],"both":[33],"long-term":[34],"static":[35],"attributes":[36],"short-term":[38],"dynamic":[39],"states":[40],"derived":[41],"from":[42,59,126],"historical":[43],"interaction":[44],"logs.":[45],"Recent":[46],"Large":[47],"Language":[48,129],"Models":[49],"(LLMs)":[50],"offer":[51],"strong":[52],"long-context":[53],"reasoning":[54],"constructing":[56],"structured":[57],"profiles":[58],"these":[60,108],"logs,":[61],"but":[62],"existing":[63],"solutions":[64],"face":[65],"two":[66,144],"challenges":[67],"deployment:":[70],"(1)":[71],"profiling":[72,162],"methods":[73,163],"are":[74],"typically":[75],"domain-specific":[76],"lack":[78],"reusable":[80],"abstraction":[81],"across":[82],"service":[83],"scenarios,":[84],"(2)":[86],"fine-tuning":[87,182,213],"alignment":[88],"models":[89],"heterogeneous":[91,192],"clusters":[93],"incurs":[94],"high":[95],"synchronization":[96],"overhead":[97],"due":[98],"to":[99,168,187,209],"variance":[101],"in":[102,143],"input":[103],"sequence":[104],"lengths.":[105],"To":[106],"address":[107],"challenges,":[109],"we":[110,159,177],"propose":[111,178],"CogGuard,":[112],"proactive-warning":[114],"framework":[115],"services.":[119],"CogGuard":[120,202,234],"decouples":[121],"offline":[122],"LLM-based":[123],"profile":[124,157,204],"construction":[125,205],"online":[127],"Small":[128],"Model":[130],"(SLM)-based":[131],"score":[132],"through":[134],"shared":[136],"static-dynamic":[137],"profile-to-score":[138],"pipeline,":[139],"instantiates":[141],"it":[142],"representative":[145],"scenarios:":[146],"educational":[147,232],"performance":[148],"operational":[151],"outcome":[153],"warning.":[154],"For":[155,173],"efficient":[156],"construction,":[158],"design":[160],"scenario-specific":[161],"with":[164,184,241],"prefix-aligned":[165],"KV-cache":[166],"reuse":[167],"reduce":[169],"repeated":[170],"encoding":[171],"overhead.":[172],"edge-side":[174],"model":[175],"alignment,":[176],"length-aware":[180],"distributed":[181,212],"strategy":[183],"contrastive":[185],"regularization":[186],"mitigate":[188],"workload":[189],"imbalance":[190],"clusters.":[193],"Experiments":[194],"education":[196],"operation":[198],"datasets":[199],"show":[200],"that":[201],"reduces":[203,235],"time":[206,214],"by":[207,215,238],"up":[208],"48%":[210],"19%,":[216],"while":[217],"achieving":[218],"MAEs":[219],"of":[220],"13.4":[221],"5.9,":[223],"respectively,":[224],"100-point-scale":[226],"tasks.":[228],"In":[229],"largest":[231],"setting,":[233],"error":[237],"15.4%":[239],"compared":[240],"strongest":[243],"baseline.":[244]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-17T00:00:00"}
