{"id":"https://openalex.org/W4414909010","doi":"https://doi.org/10.1109/icdcs63083.2025.00036","title":"Efficient Partitioning Vision Transformer on Edge Devices for Distributed Inference","display_name":"Efficient Partitioning Vision Transformer on Edge Devices for Distributed Inference","publication_year":2025,"publication_date":"2025-07-21","ids":{"openalex":"https://openalex.org/W4414909010","doi":"https://doi.org/10.1109/icdcs63083.2025.00036"},"language":"en","primary_location":{"id":"doi:10.1109/icdcs63083.2025.00036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdcs63083.2025.00036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS)","raw_type":"proceedings-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/A5100394707","display_name":"Xiang Liu","orcid":"https://orcid.org/0009-0000-1777-3681"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Xiang Liu","raw_affiliation_strings":["National University of Singapore,School of Computing"],"affiliations":[{"raw_affiliation_string":"National University of Singapore,School of Computing","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018170925","display_name":"Yijun Song","orcid":"https://orcid.org/0000-0003-0435-8627"},"institutions":[{"id":"https://openalex.org/I90727586","display_name":"Zhejiang University of Finance and Economics","ror":"https://ror.org/055vj5234","country_code":"CN","type":"education","lineage":["https://openalex.org/I90727586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijun Song","raw_affiliation_strings":["Zhejiang University of Finance &#x0026; Economics Dongfang College,Information and Artificial Intelligence Institute"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Finance &#x0026; Economics Dongfang College,Information and Artificial Intelligence Institute","institution_ids":["https://openalex.org/I90727586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445622","display_name":"Xia Li","orcid":"https://orcid.org/0000-0003-3050-8529"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Xia Li","raw_affiliation_strings":["ETH Zurich,Department of Computer Science"],"affiliations":[{"raw_affiliation_string":"ETH Zurich,Department of Computer Science","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078704429","display_name":"Yifei Sun","orcid":"https://orcid.org/0000-0002-6961-5500"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifei Sun","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081598354","display_name":"Huiying Lan","orcid":"https://orcid.org/0000-0003-3120-5773"},"institutions":[{"id":"https://openalex.org/I100162341","display_name":"Luminex (United States)","ror":"https://ror.org/03fef0h61","country_code":"US","type":"company","lineage":["https://openalex.org/I100162341"]},{"id":"https://openalex.org/I4210162847","display_name":"Lumen (United Kingdom)","ror":"https://ror.org/05fexxx29","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210162847"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Huiying Lan","raw_affiliation_strings":["Lumia Ltd"],"affiliations":[{"raw_affiliation_string":"Lumia Ltd","institution_ids":["https://openalex.org/I100162341","https://openalex.org/I4210162847"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101992934","display_name":"Zemin Liu","orcid":"https://orcid.org/0000-0002-2261-2812"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zemin Liu","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039197863","display_name":"Linshan Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Linshan Jiang","raw_affiliation_strings":["National University of Singapore,Institute of Data Science"],"affiliations":[{"raw_affiliation_string":"National University of Singapore,Institute of Data Science","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108050353","display_name":"Jialin Li","orcid":"https://orcid.org/0000-0002-5879-8954"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jialin Li","raw_affiliation_strings":["National University of Singapore,School of Computing"],"affiliations":[{"raw_affiliation_string":"National University of Singapore,School of Computing","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100394707"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":1.3947,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84536133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"286","last_page":"296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9753999710083008,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.8238999843597412},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.555400013923645},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5006999969482422},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.49799999594688416},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4075999855995178},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4074999988079071},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.3815000057220459},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3402000069618225},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.3384999930858612}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8238999843597412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722599983215332},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.555400013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.525600016117096},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5006999969482422},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.49799999594688416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45500001311302185},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3833000063896179},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.29350000619888306},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C161334170","wikidata":"https://www.wikidata.org/wiki/Q1428778","display_name":"Smart camera","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdcs63083.2025.00036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdcs63083.2025.00036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2133824856","https://openalex.org/W2593116425","https://openalex.org/W2963563276","https://openalex.org/W3049455300","https://openalex.org/W3096609285","https://openalex.org/W3099971873","https://openalex.org/W3165924482","https://openalex.org/W3171516518","https://openalex.org/W3188427387","https://openalex.org/W3203700770","https://openalex.org/W3206996142","https://openalex.org/W4226126941","https://openalex.org/W4285327057","https://openalex.org/W4312847199","https://openalex.org/W4313170858","https://openalex.org/W4320008754","https://openalex.org/W4365446402","https://openalex.org/W4386072014","https://openalex.org/W4386699354","https://openalex.org/W4387211045","https://openalex.org/W4390873032","https://openalex.org/W4402715912"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"models":[2,44,80,185],"are":[3],"increasingly":[4],"utilized":[5],"on":[6,45,120,130,143,186],"resource-constrained":[7,46],"edge":[8,47,72,131,144,187],"devices":[9,145],"for":[10,41],"real-time":[11],"data":[12,93],"analytics.":[13],"Recently,":[14],"Vision":[15,68,78,170],"Transformer":[16,79],"and":[17,34,65,100,127,146,158,183,196],"their":[18,30],"variants":[19],"have":[20],"shown":[21],"exceptional":[22],"performance":[23],"in":[24,150],"various":[25],"computer":[26],"vision":[27],"tasks.":[28],"However,":[29],"substantial":[31],"computational":[32,98],"requirements":[33],"low":[35],"inference":[36,101,141,194],"latency":[37,142],"create":[38],"significant":[39],"challenges":[40],"deploying":[42],"such":[43,191],"devices.":[48,73],"To":[49,95],"address":[50],"this":[51],"issue,":[52],"we":[53,103,133,173],"propose":[54],"a":[55,89,105,148],"novel":[56],"framework,":[57],"ED-ViT,":[58],"which":[59],"is":[60],"designed":[61],"to":[62,87,155,167],"efficiently":[63],"split":[64],"execute":[66],"complex":[67],"Transformers":[69],"across":[70],"multiple":[71],"Our":[74,200],"approach":[75],"involves":[76],"partitioning":[77],"into":[81],"several":[82],"sub-models,":[83],"while":[84,162],"each":[85,114],"dedicated":[86],"handling":[88],"specific":[90],"subset":[91],"of":[92,113,206],"classes.":[94],"further":[96],"reduce":[97],"overhead":[99],"latency,":[102],"introduce":[104],"class-wise":[106],"pruning":[107],"technique":[108],"that":[109,135,180],"decreases":[110],"the":[111,168,204,207],"size":[112,152],"sub-model.":[115],"Through":[116],"extensive":[117],"experiments":[118],"conducted":[119],"five":[121],"datasets":[122],"using":[123],"three":[124],"model":[125,151,198],"architectures":[126],"actual":[128],"implementation":[129],"devices,":[132,188],"demonstrate":[134],"our":[136],"method":[137],"significantly":[138],"cuts":[139],"down":[140],"achieves":[147],"reduction":[149],"by":[153],"up":[154],"28.9":[156],"times":[157],"34.1":[159],"times,":[160],"respectively,":[161],"maintaining":[163],"test":[164],"accuracy":[165],"comparable":[166],"original":[169],"Transformer.":[171],"Additionally,":[172],"compare":[174],"ED-ViT":[175,209],"with":[176],"two":[177],"state-of-the-art":[178],"methods":[179],"deploy":[181],"CNN":[182],"SNN":[184],"evaluating":[189],"metrics":[190],"as":[192],"accuracy,":[193],"time,":[195],"overall":[197],"size.":[199],"comprehensive":[201],"evaluation":[202],"underscores":[203],"effectiveness":[205],"proposed":[208],"framework.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
