{"id":"https://openalex.org/W2996752431","doi":"https://doi.org/10.1109/globecom38437.2019.9014056","title":"An Efficient Distributed Deep Learning Framework for Fog-Based IoT Systems","display_name":"An Efficient Distributed Deep Learning Framework for Fog-Based IoT Systems","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2996752431","doi":"https://doi.org/10.1109/globecom38437.2019.9014056","mag":"2996752431"},"language":"en","primary_location":{"id":"doi:10.1109/globecom38437.2019.9014056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9014056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5002187549","display_name":"Yijia Chang","orcid":"https://orcid.org/0009-0008-4999-7821"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijia Chang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080717946","display_name":"Xi Huang","orcid":"https://orcid.org/0000-0003-3391-6675"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Huang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025859650","display_name":"Ziyu Shao","orcid":"https://orcid.org/0000-0002-8774-1391"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Shao","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397725","display_name":"Yang Yang","orcid":"https://orcid.org/0000-0003-0608-9408"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9990000128746033,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9990000128746033,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9961000084877014,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7570351362228394},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6682530641555786},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5137940049171448},{"id":"https://openalex.org/keywords/fog-computing","display_name":"Fog computing","score":0.4958439767360687},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45214515924453735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33973562717437744},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.32032716274261475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7570351362228394},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6682530641555786},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5137940049171448},{"id":"https://openalex.org/C2986652147","wikidata":"https://www.wikidata.org/wiki/Q21809931","display_name":"Fog computing","level":3,"score":0.4958439767360687},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45214515924453735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33973562717437744},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.32032716274261475}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom38437.2019.9014056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9014056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1979946760","https://openalex.org/W2011032342","https://openalex.org/W2075157159","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2472333518","https://openalex.org/W2531409750","https://openalex.org/W2605258629","https://openalex.org/W2612445135","https://openalex.org/W2618530766","https://openalex.org/W2809251854","https://openalex.org/W2912654452","https://openalex.org/W2921965200","https://openalex.org/W2962677625","https://openalex.org/W2962883027","https://openalex.org/W2963477586","https://openalex.org/W2963677766","https://openalex.org/W2964248614","https://openalex.org/W2979359324","https://openalex.org/W3017598548","https://openalex.org/W3118608800","https://openalex.org/W4235765578","https://openalex.org/W4297775537","https://openalex.org/W4299997110","https://openalex.org/W6629815555","https://openalex.org/W6737664043","https://openalex.org/W6738279954","https://openalex.org/W6776359626"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W2939353110","https://openalex.org/W3009238340","https://openalex.org/W2900070427","https://openalex.org/W3095247034","https://openalex.org/W2618984630","https://openalex.org/W2958794440","https://openalex.org/W4225852903","https://openalex.org/W2908407949"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"are":[4],"the":[5,40,89,132,194,200],"key":[6],"techniques":[7,37,190],"to":[8,17,38,58,78,105,111,130,144,174,191],"enable":[9],"edge/fog":[10],"intelligence.":[11],"By":[12,164],"far,":[13],"it":[14],"remains":[15],"challenging":[16],"conduct":[18,175],"distributed":[19,125],"deployment":[20],"of":[21,62,72,92,202,218],"DNN":[22],"models":[23],"onto":[24,64],"resource-constrained":[25],"fog":[26,44,65,79,149],"nodes":[27,150],"with":[28,215],"low":[29],"latency.":[30],"Existing":[31],"solutions":[32],"adopt":[33,137],"either":[34],"model":[35,48,96,99,179],"compression":[36,102],"reduce":[39,145],"computation":[41,56,146,210],"loads":[42,147],"on":[43,148],"nodes,":[45,80],"or":[46],"horizontal":[47,83,95,176],"partition":[49,59,84,100,180],"techniques,":[50,168],"which":[51,81],"exploit":[52],"particular":[53,73],"communication":[54],"and":[55,86,94,101,161,177,187,212],"patterns":[57],"different":[60],"layers":[61,74],"DNNs":[63,157],"nodes.":[66],"Nonetheless,":[67],"sometimes":[68],"even":[69],"resource":[70],"demands":[71],"can":[75],"be":[76],"unaffordable":[77],"makes":[82],"inadequate":[85],"calls":[87],"for":[88],"joint":[90],"design":[91,141],"vertical":[93,178],"partition.":[97],"Besides,":[98],"may":[103],"lead":[104],"degraded":[106],"inference":[107,195,219],"accuracy,":[108],"but":[109],"approaches":[110],"compensate":[112],"such":[113],"accuracy":[114],"loss":[115,217],"remain":[116],"unexplored.In":[117],"this":[118],"paper,":[119],"we":[120,136,169,183],"propose":[121,170],"an":[122],"integrated":[123],"efficient":[124],"deep":[126],"learning":[127,186,189],"(EDDL)":[128],"framework":[129,204],"address":[131],"above":[133],"challenges.":[134],"Particularly,":[135],"balanced":[138],"incomplete":[139],"block":[140],"(BIBD)":[142],"methods":[143],"by":[151],"removing":[152],"some":[153],"data":[154],"flows":[155],"in":[156,158,205,209],"a":[159,171],"systematic":[160],"structured":[162],"manner.":[163],"leveraging":[165],"grouped":[166],"convolution":[167],"practical":[172],"scheme":[173],"jointly.":[181],"Moreover,":[182],"integrate":[184],"multi-task":[185],"ensemble":[188],"further":[192],"improve":[193],"accuracy.":[196,220],"Simulation":[197],"results":[198],"verify":[199],"effectiveness":[201],"EDDL":[203],"achieving":[206],"notable":[207],"reduction":[208],"load":[211],"memory":[213],"footprint":[214],"mild":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
