{"id":"https://openalex.org/W3097366647","doi":"https://doi.org/10.1109/access.2020.3033771","title":"An Accelerated Edge Cloud System for Energy Data Stream Processing Based on Adaptive Incremental Deep Learning Scheme","display_name":"An Accelerated Edge Cloud System for Energy Data Stream Processing Based on Adaptive Incremental Deep Learning Scheme","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3097366647","doi":"https://doi.org/10.1109/access.2020.3033771","mag":"3097366647"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033771","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09239387.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09239387.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100654659","display_name":"Seong-Hwan Kim","orcid":"https://orcid.org/0000-0002-3842-3821"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Hwan Kim","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100731256","display_name":"Changha Lee","orcid":"https://orcid.org/0000-0003-3687-2989"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Changha Lee","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045403869","display_name":"Chan\u2010Hyun Youn","orcid":"https://orcid.org/0000-0002-3970-7308"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chan-Hyun Youn","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850,"provenance":"doaj"},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850,"provenance":"doaj"},"fwci":0.595,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":7,"citation_normalized_percentile":{"value":0.744604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":82,"max":84},"biblio":{"volume":"8","issue":null,"first_page":"195341","last_page":"195358"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9994,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9994,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9986,"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/T12676","display_name":"Machine Learning and ELM","score":0.9977,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5607655},{"id":"https://openalex.org/keywords/stream-processing","display_name":"Stream Processing","score":0.43035448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814721},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6334089},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5852718},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5607655},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.54003},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.52566725},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.44651288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44311112},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.44305888},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43538335},{"id":"https://openalex.org/C107027933","wikidata":"https://www.wikidata.org/wiki/Q2006448","display_name":"Stream processing","level":2,"score":0.43035448},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4102345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4050681},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2540388},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.14797914},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033771","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09239387.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/0e0ea54c139742bc9bf4ca795e13b88d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3033771","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09239387.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.63}],"grants":[{"funder":"https://openalex.org/F4320326258","funder_display_name":"Korea Electric Power Corporation","award_id":"R18XA05"}],"datasets":[],"versions":[],"referenced_works_count":40,"referenced_works":["https://openalex.org/W1537764194","https://openalex.org/W1947481528","https://openalex.org/W1985157189","https://openalex.org/W1987644148","https://openalex.org/W2009588584","https://openalex.org/W2022775778","https://openalex.org/W2028788479","https://openalex.org/W2037242621","https://openalex.org/W2044857874","https://openalex.org/W2063554643","https://openalex.org/W2069701377","https://openalex.org/W2094756095","https://openalex.org/W2102486516","https://openalex.org/W2125282910","https://openalex.org/W2131400476","https://openalex.org/W2163150789","https://openalex.org/W2296319761","https://openalex.org/W2407374891","https://openalex.org/W2520599539","https://openalex.org/W2523246573","https://openalex.org/W2552500151","https://openalex.org/W2585560244","https://openalex.org/W2588336250","https://openalex.org/W2744829609","https://openalex.org/W2762597430","https://openalex.org/W2782970864","https://openalex.org/W2787839606","https://openalex.org/W2798515322","https://openalex.org/W2803403013","https://openalex.org/W2812669263","https://openalex.org/W2883929540","https://openalex.org/W2893890695","https://openalex.org/W2917322258","https://openalex.org/W2948490758","https://openalex.org/W2963258546","https://openalex.org/W2963433607","https://openalex.org/W2964108773","https://openalex.org/W2967531349","https://openalex.org/W4250589301","https://openalex.org/W4255466416"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4313526662","https://openalex.org/W4313463379","https://openalex.org/W4312996489","https://openalex.org/W4238233472","https://openalex.org/W4205963435","https://openalex.org/W3216099748","https://openalex.org/W3111395152","https://openalex.org/W3106131444","https://openalex.org/W2893963003"],"abstract_inverted_index":{"As":[0],"smart":[1,28,81],"metering":[2,37,41],"technology":[3],"evolves,":[4],"power":[5,14,58],"suppliers":[6],"can":[7],"make":[8],"low-cost,":[9],"low-risk":[10],"estimation":[11],"of":[12,89,96,114,134,193,208],"customer-side":[13],"consumption":[15],"by":[16,137],"analyzing":[17],"energy":[18,36,135],"demand":[19,136],"data":[20,68,97,103,110,154],"collected":[21],"in":[22,185],"real-time.":[23],"With":[24],"advances":[25],"network":[26],"infrastructure,":[27,38],"sensors,":[29],"and":[30,47,83,170,244,259],"various":[31,218],"monitoring":[32],"technologies,":[33],"a":[34,87,93,101,147,156,213,251,255],"standardized":[35],"called":[39],"advanced":[40],"infrastructure":[42,84],"(AMI),":[43],"has":[44],"been":[45],"introduced":[46],"deployed":[48],"to":[49,52,55,62,112,188,200,204],"urban":[50],"households":[51],"allow":[53],"them":[54],"develop":[56],"efficient":[57,264],"generation":[59,111],"plans.":[60],"Compared":[61],"traditional":[63],"stochastic":[64],"approaches":[65],"for":[66,131,221,240,246],"time-series":[67],"analysis,":[69],"deep-learning":[70,115,171,223],"methods":[71],"have":[72],"shown":[73],"superior":[74],"accuracy":[75],"on":[76],"many":[77],"prediction":[78,133],"applications.":[79],"Because":[80],"meters":[82],"monitors":[85],"produce":[86],"series":[88],"measurements":[90],"over":[91,155],"time,":[92],"large":[94,102],"amount":[95],"is":[98,146],"accumulated,":[99],"creating":[100],"stream,":[104],"which":[105],"takes":[106],"much":[107],"time":[108,191],"from":[109],"deployment":[113],"model":[116,257],"training.":[117],"In":[118,211],"this":[119],"article,":[120],"we":[121],"propose":[122],"an":[123,165],"accelerated":[124,222],"computing":[125],"system":[126,145,150],"that":[127,151,234],"considers":[128],"time-variant":[129],"properties":[130],"accurate":[132],"processing":[138,224],"the":[139,183,190,194,205,227],"AMI":[140,153],"stream":[141],"data.":[142],"The":[143,230],"proposed":[144],"real-time":[148],"training/inference":[149],"deploys":[152],"distributed":[157],"edge":[158],"cloud.":[159],"It":[160],"comprises":[161],"two":[162],"core":[163],"components:":[164],"adaptive":[166,178,241],"incremental":[167,179,209,247],"learning":[168,180,248],"solver":[169],"acceleration":[172],"with":[173,262],"FPGA-GPU":[174],"resource":[175,214],"scheduling.":[176],"An":[177],"scheme":[181,216],"adjusts":[182],"batch/epoch":[184],"training":[186],"iteration":[187],"reduce":[189],"delay":[192],"latest":[195],"trained":[196],"model,":[197],"while":[198,225,249],"trying":[199],"prevent":[201],"biased-training":[202],"due":[203],"sub-optimal":[206],"optimizer":[207],"learning.":[210],"addition,":[212],"scheduling":[215],"manages":[217],"accelerator":[219],"resources":[220],"minimizing":[226],"computational":[228],"cost.":[229],"experimental":[231],"results":[232],"demonstrated":[233],"our":[235],"method":[236],"achieved":[237],"good":[238],"performance":[239],"batch":[242],"size":[243],"epoch":[245],"guaranteeing":[250],"low":[252],"inference":[253],"error,":[254],"high":[256],"score,":[258],"queue":[260],"stability":[261],"cost":[263],"processing.":[265]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3097366647","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2024-12-11T07:36:59.138324","created_date":"2020-11-09"}