{"id":"https://openalex.org/W4393422150","doi":"https://doi.org/10.1145/3656041","title":"EdgeCI: Distributed Workload Assignment and Model Partitioning for CNN Inference on Edge Clusters","display_name":"EdgeCI: Distributed Workload Assignment and Model Partitioning for CNN Inference on Edge Clusters","publication_year":2024,"publication_date":"2024-04-02","ids":{"openalex":"https://openalex.org/W4393422150","doi":"https://doi.org/10.1145/3656041"},"language":"en","primary_location":{"id":"doi:10.1145/3656041","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3656041","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3656041","source":{"id":"https://openalex.org/S97833917","display_name":"ACM Transactions on Internet Technology","issn_l":"1533-5399","issn":["1533-5399","1557-6051"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Internet Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3656041","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100733227","display_name":"Yanming Chen","orcid":"https://orcid.org/0000-0002-2747-6637"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanming Chen","raw_affiliation_strings":["School of Compute Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-2747-6637","affiliations":[{"raw_affiliation_string":"School of Compute Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107229708","display_name":"Tong Luo","orcid":"https://orcid.org/0009-0002-5541-0341"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Luo","raw_affiliation_strings":["School of Compute Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0002-5541-0341","affiliations":[{"raw_affiliation_string":"School of Compute Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033185885","display_name":"Weiwei Fang","orcid":"https://orcid.org/0000-0002-6407-7467"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Fang","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Jiaotong University, Haidian, China"],"raw_orcid":"https://orcid.org/0000-0002-6407-7467","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Haidian, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103216531","display_name":"Naixue Xiong","orcid":"https://orcid.org/0000-0002-0394-4635"},"institutions":[{"id":"https://openalex.org/I162709352","display_name":"Sul Ross State University","ror":"https://ror.org/03x7qhw59","country_code":"US","type":"education","lineage":["https://openalex.org/I162709352"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neal. N. Xiong","raw_affiliation_strings":["Department of Computer Science and Mathematics, Sul Ross State University, Alpine, United States"],"raw_orcid":"https://orcid.org/0000-0002-0394-4635","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Mathematics, Sul Ross State University, Alpine, United States","institution_ids":["https://openalex.org/I162709352"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100733227"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":2.2438,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88771292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"24","issue":"2","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9976999759674072,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9250530004501343},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.6219916939735413},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5933000445365906},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5535740852355957},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.41835644841194153},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39406752586364746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3683125376701355},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.34273070096969604},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1408291757106781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9250530004501343},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.6219916939735413},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5933000445365906},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5535740852355957},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.41835644841194153},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39406752586364746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3683125376701355},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.34273070096969604},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1408291757106781}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3656041","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3656041","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3656041","source":{"id":"https://openalex.org/S97833917","display_name":"ACM Transactions on Internet Technology","issn_l":"1533-5399","issn":["1533-5399","1557-6051"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Internet Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3656041","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3656041","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3656041","source":{"id":"https://openalex.org/S97833917","display_name":"ACM Transactions on Internet Technology","issn_l":"1533-5399","issn":["1533-5399","1557-6051"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Internet Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2898341671","display_name":null,"funder_award_id":"62172031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393422150.pdf","grobid_xml":"https://content.openalex.org/works/W4393422150.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2009070933","https://openalex.org/W2194775991","https://openalex.org/W2604319603","https://openalex.org/W2612193523","https://openalex.org/W2748902594","https://openalex.org/W2790412025","https://openalex.org/W2896180420","https://openalex.org/W2897303255","https://openalex.org/W2902286550","https://openalex.org/W2919629997","https://openalex.org/W2920031528","https://openalex.org/W2950865323","https://openalex.org/W2962883027","https://openalex.org/W2966968590","https://openalex.org/W2981587265","https://openalex.org/W2983440318","https://openalex.org/W3005276590","https://openalex.org/W3010833785","https://openalex.org/W3012561096","https://openalex.org/W3014798366","https://openalex.org/W3017807730","https://openalex.org/W3047565185","https://openalex.org/W3094019951","https://openalex.org/W3110777925","https://openalex.org/W3111395152","https://openalex.org/W3114323021","https://openalex.org/W3130823781","https://openalex.org/W4213343903","https://openalex.org/W4221146321","https://openalex.org/W4236099117","https://openalex.org/W4281554877","https://openalex.org/W4283215460","https://openalex.org/W4285082282","https://openalex.org/W4288084599","https://openalex.org/W4290973886","https://openalex.org/W4295872615","https://openalex.org/W4302806412","https://openalex.org/W4308360138","https://openalex.org/W4309765727","https://openalex.org/W4320005531","https://openalex.org/W4362690361","https://openalex.org/W4385245983","https://openalex.org/W4390187455"],"related_works":["https://openalex.org/W2000785801","https://openalex.org/W986318368","https://openalex.org/W2384410913","https://openalex.org/W2352878646","https://openalex.org/W2004734601","https://openalex.org/W2130149817","https://openalex.org/W2990194547","https://openalex.org/W1480123525","https://openalex.org/W2620865396","https://openalex.org/W2414054180"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"technology":[2],"has":[3],"grown":[4],"significantly":[5],"in":[6],"new":[7],"application":[8],"scenarios":[9],"such":[10],"as":[11],"smart":[12],"cities":[13],"and":[14,67,95,156,162,175],"driverless":[15],"vehicles,":[16],"but":[17],"its":[18,158],"deployment":[19],"needs":[20],"to":[21,31,42,54,64,78,91,124,194],"consume":[22],"a":[23,80],"lot":[24],"of":[25],"resources.":[26],"It":[27],"is":[28,51,141],"usually":[29,52],"difficult":[30],"execute":[32],"inference":[33,49,84,89,147,190],"task":[34,50],"solely":[35],"on":[36,135,154,202],"resource-constrained":[37,96],"Intelligent":[38],"Internet-of-Things":[39],"(IoT)":[40],"devices":[41],"meet":[43],"strictly":[44],"service":[45],"delay":[46],"requirements.":[47],"CNN-based":[48],"offloaded":[53],"the":[55,72,116,125,146,178,198],"edge":[56,204],"server":[57],"or":[58],"cloud.":[59],"However,":[60],"it":[61],"may":[62],"lead":[63],"unstable":[65],"performance":[66,159],"privacy":[68],"leaks.":[69],"To":[70],"address":[71],"above":[73],"challenges,":[74],"this":[75],"article":[76],"aims":[77],"design":[79],"low":[81],"latency":[82],"distributed":[83],"framework,":[85],"EdgeCI,":[86],"which":[87,114,140],"assigns":[88],"tasks":[90],"locally":[92],"idle,":[93],"connected,":[94],"IoT":[97,128],"device":[98],"cluster":[99],"networks.":[100],"EdgeCI":[101,152,187,196],"exploits":[102],"two":[103],"key":[104],"optimization":[105],"knobs,":[106],"including:":[107],"(1)":[108],"Auction-based":[109],"Workload":[110],"Assignment":[111],"Scheme":[112],"(AWAS),":[113],"achieves":[115],"workload":[117,122],"balance":[118],"by":[119,192],"assigning":[120],"each":[121],"partition":[123],"more":[126],"matching":[127],"device;":[129],"(2)":[130],"Fused-Layer":[131],"parallelization":[132],"strategy":[133],"based":[134,153],"non-recursive":[136],"Dynamic":[137],"Programming":[138],"(DPFL),":[139],"aimed":[142],"at":[143],"further":[144],"minimizing":[145],"time.":[148],"We":[149],"have":[150],"implemented":[151],"PyTorch":[155],"evaluated":[157],"with":[160],"VGG-16":[161],"ResNet-34":[163],"image":[164],"recognition":[165],"models.":[166],"The":[167],"experimental":[168],"results":[169],"prove":[170],"that":[171],"our":[172,203],"proposed":[173],"AWAS":[174],"DPFL":[176],"outperform":[177],"typical":[179],"state-of-the-art":[180],"solutions.":[181],"When":[182],"they":[183],"are":[184],"well":[185],"combined,":[186],"can":[188],"improve":[189],"speed":[191],"34.72%":[193],"43.52%.":[195],"outperforms":[197],"state-of-the":[199],"art":[200],"approaches":[201],"cluster.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}