{"id":"https://openalex.org/W4408323736","doi":"https://doi.org/10.1109/jiot.2025.3550162","title":"Loss-Adapter: Addressing Network Packet Loss in Distributed Inference for Lossy IoT Environments","display_name":"Loss-Adapter: Addressing Network Packet Loss in Distributed Inference for Lossy IoT Environments","publication_year":2025,"publication_date":"2025-03-11","ids":{"openalex":"https://openalex.org/W4408323736","doi":"https://doi.org/10.1109/jiot.2025.3550162"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3550162","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3550162","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-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":null,"display_name":"Zhangcheng Hou","orcid":"https://orcid.org/0009-0005-6503-7175"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhangcheng Hou","raw_affiliation_strings":["Faculty of Science and Technology, Keio University, Yokohama, Japan"],"raw_orcid":"https://orcid.org/0009-0005-6503-7175","affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016337773","display_name":"Tomoaki Ohtsuki","orcid":"https://orcid.org/0000-0003-3961-1426"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Ohtsuki","raw_affiliation_strings":["Faculty of Science and Technology, Keio University, Yokohama, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3961-1426","affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.9389,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73056223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"12","issue":"12","first_page":"22048","last_page":"22057"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9796000123023987,"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":0.9796000123023987,"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/T11478","display_name":"Caching and Content Delivery","score":0.9664000272750854,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.965499997138977,"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/lossy-compression","display_name":"Lossy compression","score":0.8550267815589905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8482494354248047},{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.7774866819381714},{"id":"https://openalex.org/keywords/packet-loss","display_name":"Packet loss","score":0.6874355673789978},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.6478560566902161},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5063246488571167},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.49855661392211914},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.49395304918289185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11501574516296387},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.11492764949798584}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.8550267815589905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8482494354248047},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.7774866819381714},{"id":"https://openalex.org/C54108766","wikidata":"https://www.wikidata.org/wiki/Q391064","display_name":"Packet loss","level":3,"score":0.6874355673789978},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.6478560566902161},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5063246488571167},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.49855661392211914},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.49395304918289185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11501574516296387},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.11492764949798584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3550162","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3550162","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8635182443","display_name":"Intelligent wireless communication system based on Transformer","funder_award_id":"24K00888","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W208085512","https://openalex.org/W1984980195","https://openalex.org/W2194775991","https://openalex.org/W2798956872","https://openalex.org/W2808976322","https://openalex.org/W2896180420","https://openalex.org/W2919115771","https://openalex.org/W2960833983","https://openalex.org/W2962883027","https://openalex.org/W2969236120","https://openalex.org/W2981494784","https://openalex.org/W3014798366","https://openalex.org/W3043914740","https://openalex.org/W3090796351","https://openalex.org/W3158049700","https://openalex.org/W3167490029","https://openalex.org/W3182501581","https://openalex.org/W4205369066","https://openalex.org/W4205999233","https://openalex.org/W4210839873","https://openalex.org/W4226206247","https://openalex.org/W4283204791","https://openalex.org/W4283214771","https://openalex.org/W4295872615","https://openalex.org/W4308507008","https://openalex.org/W4362612860","https://openalex.org/W4389722428","https://openalex.org/W4393105094","https://openalex.org/W4399665748","https://openalex.org/W6640036494","https://openalex.org/W6676179485","https://openalex.org/W6739369274","https://openalex.org/W6742075157","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W2133028525","https://openalex.org/W4229060448","https://openalex.org/W4306381730","https://openalex.org/W2981692913","https://openalex.org/W1995805316","https://openalex.org/W2387503788","https://openalex.org/W3044188621","https://openalex.org/W3184035966","https://openalex.org/W2059658550","https://openalex.org/W3199712142"],"abstract_inverted_index":{"The":[0],"deployment":[1],"of":[2,10,82,106,132,151,174],"deep":[3],"neural":[4],"networks":[5],"(DNNs)":[6],"in":[7,36,66],"the":[8,22,67,80,104,107,123,130,133,149,152,167,171],"Internet":[9],"Things":[11],"(IoT)":[12],"is":[13,101],"essential":[14],"for":[15,25,62,114],"various":[16],"AI":[17],"applications.":[18],"This":[19,99],"trend":[20],"highlights":[21],"growing":[23],"need":[24],"distributed":[26],"inference":[27,47,112,160,172],"(DI)":[28],"capabilities":[29,113],"to":[30,56,78,109,128,145],"process":[31],"data":[32,42],"efficiently":[33],"and":[34,156],"effectively":[35],"IoT":[37,140,180],"environments.":[38],"In":[39],"lossy":[40,85,179],"networks,":[41],"loss":[43,142],"can":[44],"significantly":[45,169],"affect":[46],"accuracy.":[48,161],"Prioritizing":[49],"algorithmic":[50],"optimizations":[51],"over":[52,116],"hardware":[53],"modifications":[54],"proves":[55],"be":[57],"a":[58,71,94],"more":[59],"effective":[60],"approach":[61],"enhancing":[63],"DNN":[64,153,175],"performance":[65],"IoT.":[68],"We":[69,137],"propose":[70],"plug-and-play":[72],"module":[73],"called":[74],"Loss-Adapter,":[75],"which":[76],"aims":[77],"improve":[79],"accuracy":[81,173],"DI":[83],"on":[84,159,178],"networks.":[86,181],"To":[87],"simulate":[88],"network":[89],"packet":[90,141,157],"loss,":[91],"we":[92,121],"design":[93,138],"Gaussian":[95,134],"distribution":[96],"sampling":[97],"dropout.":[98],"method":[100],"utilized":[102],"during":[103],"training":[105],"Loss-Adapter":[108,168],"acquire":[110],"fault-tolerant":[111],"operation":[115],"unreliable":[117],"communication":[118],"links.":[119],"Moreover,":[120],"employ":[122],"tree-structured":[124],"Parzen":[125],"estimator":[126],"algorithm":[127],"optimize":[129],"parameters":[131],"dropout":[135],"layer.":[136],"two":[139],"simulation":[143],"systems":[144],"conduct":[146],"experiments,":[147],"exploring":[148],"impact":[150],"split":[154],"position":[155],"size":[158],"Our":[162],"experiments":[163],"demonstrate":[164],"that":[165],"applying":[166],"enhances":[170],"models":[176],"operating":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
