{"id":"https://openalex.org/W4413677353","doi":"https://doi.org/10.1109/tmc.2025.3602966","title":"Learning the Optimal Path and DNN Partition for Collaborative Edge Inference","display_name":"Learning the Optimal Path and DNN Partition for Collaborative Edge Inference","publication_year":2025,"publication_date":"2025-08-26","ids":{"openalex":"https://openalex.org/W4413677353","doi":"https://doi.org/10.1109/tmc.2025.3602966"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2025.3602966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3602966","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100956854","display_name":"Yin Huang","orcid":"https://orcid.org/0009-0005-6024-8491"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]},{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yin Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA","Department of Electrical and Computer Engineering, University of Miami, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101664150","display_name":"Letian Zhang","orcid":"https://orcid.org/0009-0007-4340-8742"},"institutions":[{"id":"https://openalex.org/I169615421","display_name":"Middle Tennessee State University","ror":"https://ror.org/02n1hzn07","country_code":"US","type":"education","lineage":["https://openalex.org/I169615421"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Letian Zhang","raw_affiliation_strings":["Department of Computer Science, Middle Tennessee State University, Murfreesboro, TN, USA","Department of Computer Science, Middle Tennessee State University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Middle Tennessee State University, Murfreesboro, TN, USA","institution_ids":["https://openalex.org/I169615421"]},{"raw_affiliation_string":"Department of Computer Science, Middle Tennessee State University, USA","institution_ids":["https://openalex.org/I169615421"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044771462","display_name":"Jie Xu","orcid":"https://orcid.org/0000-0002-0515-1647"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]},{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA","Department of Electrical and Computer Engineering, University of Miami, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100956854"],"corresponding_institution_ids":["https://openalex.org/I145608581","https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21335851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"2","first_page":"1499","last_page":"1512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.807699978351593,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.807699978351593,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.7656000256538391,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.6707000136375427,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7942399978637695},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6006482243537903},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5975484848022461},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5468062162399292},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5280877947807312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42971283197402954},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36454668641090393},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.26722943782806396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14045122265815735},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08112350106239319}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7942399978637695},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6006482243537903},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5975484848022461},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5468062162399292},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5280877947807312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42971283197402954},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36454668641090393},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.26722943782806396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14045122265815735},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08112350106239319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2025.3602966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3602966","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1904504745","https://openalex.org/W2077902449","https://openalex.org/W2111619626","https://openalex.org/W2128421120","https://openalex.org/W2168405694","https://openalex.org/W2194775991","https://openalex.org/W2472333518","https://openalex.org/W2482293012","https://openalex.org/W2604319603","https://openalex.org/W2794925984","https://openalex.org/W2896180420","https://openalex.org/W2918714081","https://openalex.org/W2920031528","https://openalex.org/W2950929549","https://openalex.org/W2963037989","https://openalex.org/W2964015972","https://openalex.org/W2970092032","https://openalex.org/W2971714613","https://openalex.org/W2980856918","https://openalex.org/W2981114133","https://openalex.org/W3011134162","https://openalex.org/W3014364938","https://openalex.org/W3019721760","https://openalex.org/W3047565185","https://openalex.org/W3094019951","https://openalex.org/W3110777925","https://openalex.org/W3153345798","https://openalex.org/W4220806559","https://openalex.org/W4221146321","https://openalex.org/W4236099117","https://openalex.org/W4295872615","https://openalex.org/W4376481324","https://openalex.org/W4377716219","https://openalex.org/W4385489040","https://openalex.org/W4386260591","https://openalex.org/W4391164333","https://openalex.org/W4403826595"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W3161249280","https://openalex.org/W2267059662","https://openalex.org/W2364268683","https://openalex.org/W4388411807","https://openalex.org/W1519906715","https://openalex.org/W2478803962","https://openalex.org/W3169430512","https://openalex.org/W1986418932","https://openalex.org/W2357796999"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,165],"Deep":[3],"Neural":[4],"Networks":[5],"(DNNs)":[6],"have":[7],"enabled":[8],"a":[9,32,60,129,139],"wide":[10],"range":[11],"of":[12],"intelligent":[13],"mobile":[14],"applications,":[15],"but":[16],"their":[17],"computational":[18],"demands":[19],"pose":[20],"challenges":[21],"for":[22,92],"resource-constrained":[23],"devices.":[24],"Collaborative":[25],"edge":[26,167],"inference":[27,34],"addresses":[28],"this":[29,56],"by":[30],"partitioning":[31],"DNN":[33,85],"task":[35],"into":[36],"several":[37],"subtasks":[38],"across":[39],"multiple":[40,70],"network":[41,49,65],"nodes.":[42],"However,":[43],"most":[44],"existing":[45,163],"methods":[46,164],"assume":[47],"known":[48],"parameters":[50,66],"or":[51],"fixed":[52],"processing":[53],"paths.":[54],"In":[55],"paper,":[57],"we":[58,136],"consider":[59],"more":[61],"complex":[62],"setting":[63],"where":[64,126],"are":[67,72],"unknown":[68],"and":[69,83,95,148,150],"paths":[71],"available.":[73],"The":[74],"goal":[75],"is":[76],"to":[77,106],"learn":[78],"both":[79],"the":[80,84,108,114],"optimal":[81],"path":[82],"layer":[86],"assignment":[87],"along":[88],"it,":[89],"while":[90],"accounting":[91],"security":[93],"threats":[94],"path-switching":[96],"costs.":[97],"We":[98,111],"first":[99],"derive":[100],"structural":[101],"insights":[102],"under":[103],"full":[104],"information":[105],"reduce":[107],"decision":[109],"space.":[110],"then":[112],"formulate":[113],"learning":[115],"problem":[116],"as":[117],"an":[118],"adversarial":[119],"group":[120],"linear":[121],"bandit":[122],"with":[123],"switching":[124],"costs,":[125],"rewards":[127],"follow":[128],"hybrid":[130],"stochastic-adversarial":[131],"process.":[132],"To":[133],"solve":[134],"this,":[135],"propose":[137],"B-EXPUCB,":[138],"new":[140],"algorithm":[141],"that":[142,152,160],"combines":[143],"ideas":[144],"from":[145],"blocked":[146],"EXP3":[147],"LinUCB,":[149],"show":[151],"it":[153],"achieves":[154],"sublinear":[155],"regret.":[156],"Extensive":[157],"simulations":[158],"demonstrate":[159],"B-EXPUCB":[161],"outperforms":[162],"collaborative":[166],"inference.":[168]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
