{"id":"https://openalex.org/W4413319957","doi":"https://doi.org/10.1109/fmec65595.2025.11119366","title":"Enhancing IoT Applications' Placement in the Fog with Proactive Infeasibility Detection and Repair","display_name":"Enhancing IoT Applications' Placement in the Fog with Proactive Infeasibility Detection and Repair","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4413319957","doi":"https://doi.org/10.1109/fmec65595.2025.11119366"},"language":"en","primary_location":{"id":"doi:10.1109/fmec65595.2025.11119366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fmec65595.2025.11119366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Fog and Mobile Edge Computing (FMEC)","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/A5083608223","display_name":"Ye Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye Xia","raw_affiliation_strings":["Independent Researcher,Seattle,WA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Independent Researcher,Seattle,WA,USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100399159","display_name":"Xing Zhang","orcid":"https://orcid.org/0000-0003-3589-7463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing Zhang","raw_affiliation_strings":["Independent Researcher,Seattle,WA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Independent Researcher,Seattle,WA,USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"74","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12222","display_name":"IoT-based Smart Home Systems","score":0.8295999765396118,"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"}},"topics":[{"id":"https://openalex.org/T12222","display_name":"IoT-based Smart Home Systems","score":0.8295999765396118,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.7012225985527039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6476397514343262},{"id":"https://openalex.org/keywords/fog-computing","display_name":"Fog computing","score":0.41593340039253235},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.32163912057876587}],"concepts":[{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.7012225985527039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6476397514343262},{"id":"https://openalex.org/C2986652147","wikidata":"https://www.wikidata.org/wiki/Q21809931","display_name":"Fog computing","level":3,"score":0.41593340039253235},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.32163912057876587}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fmec65595.2025.11119366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fmec65595.2025.11119366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Fog and Mobile Edge Computing (FMEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1996468745","https://openalex.org/W2295598076","https://openalex.org/W2747974859","https://openalex.org/W2810014552","https://openalex.org/W2903563268","https://openalex.org/W3128682647","https://openalex.org/W3159134414","https://openalex.org/W3177774379","https://openalex.org/W4313256945","https://openalex.org/W4316036175","https://openalex.org/W4380080543","https://openalex.org/W4394694898","https://openalex.org/W4400113994","https://openalex.org/W4401571420","https://openalex.org/W4401943241"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4245926026","https://openalex.org/W4311097251","https://openalex.org/W2586548817","https://openalex.org/W2390279801","https://openalex.org/W4396508792","https://openalex.org/W4400031139","https://openalex.org/W4285553818"],"abstract_inverted_index":{"Fog":[0],"computing":[1],"extends":[2],"processing":[3],"and":[4,118,167,179,258],"storage":[5],"resources":[6,23],"to":[7,20,46,53,88,103,131,136,154,177,213],"the":[8,11,25,34,47,67,95,104,116,121,156,181,196,205,211,236,239,260],"edge":[9],"of":[10,16,33,36,49,120,238],"network":[12],"by":[13],"making":[14,113,224],"use":[15,22],"heterogeneous":[17],"devices.":[18],"How":[19],"efficiently":[21],"in":[24,110,220,242],"fog":[26,122,231],"remains":[27],"a":[28,100,144,151,226],"challenge":[29],"not":[30,218],"only":[31],"because":[32],"complexity":[35],"selecting":[37],"appropriate":[38],"hosts":[39],"for":[40,229],"distributed":[41],"applications,":[42],"but":[43],"also":[44,64],"due":[45],"lack":[48],"guaranteed":[50],"resource":[51],"capacities":[52],"meet":[54],"all":[55],"applications'":[56],"deployment":[57],"requests.":[58],"Application":[59],"host":[60],"selection,":[61],"which":[62,80,252],"is":[63,70,81,86],"known":[65],"as":[66,73],"placement":[68,101,111,137],"problem,":[69],"typically":[71],"modeled":[72],"an":[74,127],"optimization":[75,105,138,250],"problem":[76,102],"with":[77,150,201],"hard":[78],"constraints,":[79],"computationally":[82,248],"expensive.":[83],"Therefore,":[84],"it":[85,225],"essential":[87],"ensure":[89,259],"that":[90,186,216],"valid":[91],"solutions":[92],"exist":[93,219],"(i.e.,":[94],"problem's":[96],"feasibility)":[97],"before":[98],"passing":[99],"module.":[106],"Otherwise,":[107],"potential":[108],"retries":[109],"decision":[112],"can":[114,253],"degrade":[115],"responsiveness":[117],"reliability":[119],"infrastructure.":[123],"This":[124],"paper":[125],"presents":[126],"infeasibility":[128,147,192],"repair":[129],"approach":[130,142],"avoid":[132],"inputting":[133],"infeasible":[134,244],"problems":[135,245],"modules.":[139],"The":[140],"proposed":[141,182,240],"integrates":[143],"Machine":[145],"Learning-based":[146],"detection":[148,193],"module":[149],"heuristic":[152],"algorithm":[153],"update":[155],"application":[157],"set":[158],"under":[159],"consideration.":[160],"Multiple":[161],"datasets<sup":[162],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[163,165],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup><sup":[164],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>Data":[166],"code":[168],"available":[169],"at":[170],"https://github.com/qazxiaye/InfeasibilityDetection":[171],"representing":[172],"diverse":[173],"infrastructures":[174,215],"are":[175],"generated":[176],"train":[178],"evaluate":[180],"model.":[183],"Experiments":[184],"show":[185],"our":[187],"model":[188,206,241],"achieves":[189],"86":[190],"%":[191],"accuracy,":[194],"outperforming":[195],"state-of-the-art":[197],"Large":[198],"Language":[199],"Model":[200],"few-shot":[202],"prompting.":[203],"Furthermore,":[204],"demonstrates":[207],"strong":[208],"generalizabilityit":[209],"has":[210],"capability":[212],"suit":[214],"do":[217],"its":[221],"training":[222],"data,":[223],"robust":[227],"solution":[228],"dynamic":[230],"environments.":[232],"These":[233],"results":[234],"highlight":[235],"effectiveness":[237],"identifying":[243],"without":[246],"invoking":[247],"expensive":[249],"modules,":[251],"significantly":[254],"reduce":[255],"computation":[256],"time":[257],"system's":[261],"responsiveness.":[262]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}