{"id":"https://openalex.org/W4411599767","doi":"https://doi.org/10.1109/tmc.2025.3582060","title":"AdaFlowLite: Scalable and Non-Blocking Inference on Asynchronous Mobile Data","display_name":"AdaFlowLite: Scalable and Non-Blocking Inference on Asynchronous Mobile Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411599767","doi":"https://doi.org/10.1109/tmc.2025.3582060"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2025.3582060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3582060","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/2031/fad14051-ab5b-4e80-9f93-4196adea7b30","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100684828","display_name":"Sicong Liu","orcid":"https://orcid.org/0000-0003-4402-1260"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sicong Liu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4402-1260","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114512814","display_name":"Fengmin \u4e2d\u56fd\u5927\u9646 Wu","orcid":"https://orcid.org/0009-0005-6965-623X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fengmin Wu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0005-6965-623X","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046093998","display_name":"Yuan Gao","orcid":"https://orcid.org/0000-0002-6943-8110"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078005520","display_name":"Bin Guo","orcid":"https://orcid.org/0000-0001-6097-2467"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Guo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6097-2467","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011140675","display_name":"Zimu Zhou","orcid":"https://orcid.org/0000-0002-5457-6967"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zimu Zhou","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-5457-6967","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053684989","display_name":"Hongkai Wen","orcid":"https://orcid.org/0000-0003-1159-090X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongkai Wen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-1159-090X","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100701166","display_name":"Zhiwen Yu","orcid":"https://orcid.org/0000-0002-9905-3238"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiwen Yu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9905-3238","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10840269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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":0.989799976348877,"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/T10772","display_name":"Distributed systems and fault tolerance","score":0.9847000241279602,"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":0.8819875717163086},{"id":"https://openalex.org/keywords/blocking","display_name":"Blocking (statistics)","score":0.731554388999939},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.6922406554222107},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6027710437774658},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.47224849462509155},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4503938555717468},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.4362668991088867},{"id":"https://openalex.org/keywords/mobile-telephony","display_name":"Mobile telephony","score":0.4273948669433594},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.40790748596191406},{"id":"https://openalex.org/keywords/mobile-radio","display_name":"Mobile radio","score":0.2708268165588379},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13066107034683228},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1205548346042633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8819875717163086},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.731554388999939},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.6922406554222107},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6027710437774658},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.47224849462509155},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4503938555717468},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.4362668991088867},{"id":"https://openalex.org/C95491727","wikidata":"https://www.wikidata.org/wiki/Q992968","display_name":"Mobile telephony","level":3,"score":0.4273948669433594},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40790748596191406},{"id":"https://openalex.org/C2781307350","wikidata":"https://www.wikidata.org/wiki/Q6887221","display_name":"Mobile radio","level":2,"score":0.2708268165588379},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13066107034683228},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1205548346042633}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmc.2025.3582060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3582060","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/fad14051-ab5b-4e80-9f93-4196adea7b30","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/fad14051-ab5b-4e80-9f93-4196adea7b30","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, S, Wu, F, Gao, Y, Guo, B, Zhou, Z, Wen, H & Yu, Z 2025, 'AdaFlowLite : Scalable and Non-Blocking Inference on Asynchronous Mobile Data', IEEE Transactions on Mobile Computing, vol. 24, no. 11, pp. 12206-12220. https://doi.org/10.1109/TMC.2025.3582060","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/fad14051-ab5b-4e80-9f93-4196adea7b30","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/fad14051-ab5b-4e80-9f93-4196adea7b30","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, S, Wu, F, Gao, Y, Guo, B, Zhou, Z, Wen, H & Yu, Z 2025, 'AdaFlowLite : Scalable and Non-Blocking Inference on Asynchronous Mobile Data', IEEE Transactions on Mobile Computing, vol. 24, no. 11, pp. 12206-12220. https://doi.org/10.1109/TMC.2025.3582060","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2392835431","https://openalex.org/W2116677773","https://openalex.org/W2126932387","https://openalex.org/W4210272022","https://openalex.org/W1844259124","https://openalex.org/W1974440652","https://openalex.org/W1541175715","https://openalex.org/W565993663","https://openalex.org/W2326504464","https://openalex.org/W2096709983"],"abstract_inverted_index":{"The":[0],"rise":[1],"of":[2,18,37,73,139,159,167],"mobile":[3,38,74,130,144],"devices":[4],"equipped":[5],"with":[6],"numerous":[7],"sensors,":[8],"such":[9,26],"as":[10,27,97,99,114],"LiDAR":[11],"and":[12,30,46,70,111,157,165,182,190,210],"cameras,":[13],"has":[14],"driven":[15],"the":[16,34,68,137,155],"adoption":[17],"multi-modal":[19,93,171],"deep":[20],"intelligence":[21],"for":[22,56,90],"distributed":[23,92],"sensing":[24],"tasks,":[25],"smart":[28],"cabins":[29],"driving":[31],"assistance.":[32],"However,":[33],"arrival":[35],"time":[36],"sensory":[39],"data":[40,101,184],"vary":[41],"due":[42],"to":[43,52,85,124,187,208,215,237],"modality":[44,109],"size":[45],"network":[47],"dynamics,":[48],"which":[49],"can":[50,233],"lead":[51],"delays":[53],"(if":[54,62],"waiting":[55],"slow":[57],"data)":[58],"or":[59],"accuracy":[60,212],"decline":[61],"inference":[63,89,96,204],"proceeds":[64],"without":[65,193],"waiting).":[66],"Moreover,":[67],"diversity":[69,156],"dynamic":[71],"nature":[72],"systems":[75],"exacerbate":[76],"this":[77,126,231],"challenge.":[78],"In":[79],"response,":[80],"we":[81],"present":[82],"a":[83,119,147,220],"shift":[84],"<italic":[86,120],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[87,121,133,177,199],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">opportunistic</i>":[88],"asynchronous":[91,239],"data,":[94],"enabling":[95],"soon":[98],"partial":[100],"arrives.":[102],"While":[103],"existing":[104],"methods":[105],"focus":[106],"on":[107],"optimizing":[108],"consistency":[110],"complementarity,":[112],"known":[113],"modal":[115],"affinity,":[116],"they":[117],"lack":[118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">computational</i>":[122],"approach":[123,153],"control":[125],"affinity":[127,142],"in":[128,143,223],"open-world":[129],"environments.":[131],"<inline-formula":[132,176,198],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math>${\\sf":[134,178,200],"AdaFlowLite}$</tex-math></inline-formula>":[135,179,201],"pioneers":[136],"formulation":[138],"structured":[140],"cross-modality":[141],"contexts":[145],"using":[146],"hierarchical":[148],"analysis-based":[149],"normalized":[150],"matrix.":[151],"This":[152],"accommodates":[154],"dynamics":[158],"modalities,":[160],"generalizing":[161],"across":[162],"different":[163],"types":[164],"numbers":[166],"inputs.":[168],"Employing":[169],"an":[170],"lightweight":[172],"Swin":[173],"Transformer":[174],"(MMLST),":[175],"facilitates":[180],"real-time":[181],"flexible":[183],"imputation,":[185],"adapting":[186],"various":[188],"modalities":[189],"downstream":[191],"tasks":[192],"retraining.":[194],"Experiments":[195],"show":[196],"that":[197],"significantly":[202],"reduces":[203],"latency":[205],"by":[206,213],"up":[207,214],"80.4%":[209],"enhances":[211],"62.1%,":[216],"while":[217],"achieving":[218],"nearly":[219],"50%":[221],"reduction":[222],"energy":[224],"consumption,":[225],"outperforming":[226],"status":[227],"quo":[228],"approaches.":[229],"Also,":[230],"method":[232],"enhance":[234],"LLM":[235],"performance":[236],"preprocess":[238],"data.":[240]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}