{"id":"https://openalex.org/W3128447306","doi":"https://doi.org/10.1145/3440054.3440065","title":"ICTA: Intelligent Computing Task Allocation for Efficient Deep Learning in Distributed Edge Computing System of IoT","display_name":"ICTA: Intelligent Computing Task Allocation for Efficient Deep Learning in Distributed Edge Computing System of IoT","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3128447306","doi":"https://doi.org/10.1145/3440054.3440065","mag":"3128447306"},"language":"en","primary_location":{"id":"doi:10.1145/3440054.3440065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3440054.3440065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big-data Service and Intelligent Computation","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/A5046125641","display_name":"Wei Qu","orcid":"https://orcid.org/0000-0002-8710-2450"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Qu","raw_affiliation_strings":["China Mobile Research Institute, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085416876","display_name":"Xiaolu Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolu Ding","raw_affiliation_strings":["China Mobile Research Institute, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054170567","display_name":"Kai Yang","orcid":"https://orcid.org/0000-0001-6337-1616"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Yang","raw_affiliation_strings":["China Mobile Research Institute, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018737199","display_name":"Yuanyuan Bao","orcid":"https://orcid.org/0000-0002-9204-9359"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Bao","raw_affiliation_strings":["China Mobile Research Institute, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102986531","display_name":"Wai Chen","orcid":"https://orcid.org/0000-0002-1663-2729"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wai Chen","raw_affiliation_strings":["China Mobile Research Institute, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, China","institution_ids":["https://openalex.org/I180662265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046125641"],"corresponding_institution_ids":["https://openalex.org/I180662265"],"apc_list":null,"apc_paid":null,"fwci":0.1542,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55795958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"52","issue":null,"first_page":"61","last_page":"69"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9954000115394592,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8182190656661987},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.7864155769348145},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.7233651876449585},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6502785682678223},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6256440877914429},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5329360365867615},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4242929518222809},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42143744230270386},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.37471073865890503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3673057556152344},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.21529513597488403},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.15086105465888977},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1345289945602417},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06393137574195862},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.05722588300704956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182190656661987},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.7864155769348145},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.7233651876449585},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6502785682678223},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6256440877914429},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5329360365867615},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4242929518222809},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42143744230270386},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.37471073865890503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3673057556152344},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.21529513597488403},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.15086105465888977},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1345289945602417},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06393137574195862},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.05722588300704956}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3440054.3440065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3440054.3440065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2160815625","https://openalex.org/W2166254818","https://openalex.org/W2610332124","https://openalex.org/W2753089952","https://openalex.org/W2766317792","https://openalex.org/W2795342689","https://openalex.org/W2862109329","https://openalex.org/W2950865323","https://openalex.org/W2962814013","https://openalex.org/W2963000099","https://openalex.org/W2963015168","https://openalex.org/W2963407617","https://openalex.org/W3004728759"],"related_works":["https://openalex.org/W3106131444","https://openalex.org/W4313526662","https://openalex.org/W4213230054","https://openalex.org/W3092280530","https://openalex.org/W3204740405","https://openalex.org/W3096095227","https://openalex.org/W2904860384","https://openalex.org/W4225871202","https://openalex.org/W2786070938","https://openalex.org/W2908407949"],"abstract_inverted_index":{"As":[0],"a":[1,124,164,219],"critical":[2],"part":[3],"of":[4,20,26,38,48,78,141,163,236],"distributed":[5,238],"cross-device":[6],"edge":[7,54,63,239,247],"computing":[8,10,64,240],"systems,":[9],"task":[11,49,73,96,135,166,200],"allocation":[12,74,167,201],"is":[13,109,139],"responsible":[14],"to":[15,34,69,90,115,188,204,218,245],"reasonably":[16],"map":[17],"the":[18,24,32,59,71,79,129,160,176,185,190,194,199,205,234],"computation":[19,125,148,195],"DL":[21,83],"tasks":[22],"onto":[23],"set":[25],"available":[27,86],"Internet-of-Things":[28],"(IoT)":[29],"devices,":[30,55],"with":[31],"aim":[33],"achieve":[35],"efficient":[36],"execution":[37],"deep":[39,170],"learning":[40,128,221],"(DL)":[41],"model":[42,114],"inference/training.":[43],"The":[44],"complexity":[45],"and":[46,61,85,94,134,147,157,242,249],"uncertainty":[47],"scheduling":[50,136],"on":[51,175,198],"diverse":[52],"IoT":[53],"as":[56,58],"well":[57],"dynamic":[60],"resource-constrained":[62],"environment,":[65],"make":[66],"it":[67],"hard":[68],"obtain":[70],"best":[72,206],"strategy":[75,168,202],"in":[76,98,123,184,193,213],"terms":[77],"optimal":[80,131],"matching":[81],"between":[82],"workloads":[84],"resources.":[87],"In":[88],"order":[89],"maximize":[91],"resource":[92,132,145,186],"utilization":[93],"optimize":[95],"allocation,":[97],"this":[99],"paper,":[100],"we":[101],"propose":[102],"Intelligent":[103],"Computing":[104],"Task":[105],"Allocation":[106],"(ICTA),":[107],"which":[108,182],"an":[110,214],"automatic":[111],"end-to-end":[112,215],"optimizing":[113],"allocate":[116],"proper":[117],"resources":[118],"for":[119],"each":[120],"operator":[121,191],"node":[122,192],"graph":[126,146,153,187],"by":[127,151],"long-term":[130],"management":[133],"strategies.":[137],"ICTA":[138,180,224,232],"capable":[140],"extracting":[142],"features":[143],"from":[144],"graph,":[149,196],"respectively,":[150],"using":[152],"convolutional":[154],"network":[155,172],"(GCN),":[156],"subsequently":[158],"predicting":[159],"system":[161,207,241],"performance":[162],"given":[165],"through":[169],"neural":[171],"(DNN)":[173],"based":[174,197],"extracted":[177],"features.":[178],"Finally,":[179],"decides":[181],"device":[183],"place":[189],"corresponding":[203],"performance.":[208],"Moreover,":[209],"being":[210,229],"trained":[211],"periodically":[212],"manner":[216],"according":[217],"continuous":[220],"mechanism,":[222],"GCN-based":[223],"will":[225],"become":[226],"smarter":[227],"while":[228],"used.":[230],"Therefore":[231],"facilitates":[233],"realization":[235],"intelligent":[237],"further":[243],"contributes":[244],"smart":[246],"applications":[248],"services.":[250]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
