{"id":"https://openalex.org/W1973632373","doi":"https://doi.org/10.1145/2530535","title":"Data-driven link quality prediction using link features","display_name":"Data-driven link quality prediction using link features","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W1973632373","doi":"https://doi.org/10.1145/2530535","mag":"1973632373"},"language":"en","primary_location":{"id":"doi:10.1145/2530535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2530535","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","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":"https://openalex.org/A5071128160","display_name":"Tao Liu","orcid":"https://orcid.org/0000-0002-5212-2806"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tao Liu","raw_affiliation_strings":["University of California, Merced, CA","University of California, Merced CA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California, Merced, CA","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"University of California, Merced CA#TAB#","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044884862","display_name":"Alberto Cerpa","orcid":"https://orcid.org/0000-0003-4531-9704"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alberto E. Cerpa","raw_affiliation_strings":["University of California, Merced, CA","University of California, Merced CA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of California, Merced, CA","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"University of California, Merced CA#TAB#","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5071128160"],"corresponding_institution_ids":["https://openalex.org/I156087764"],"apc_list":null,"apc_paid":null,"fwci":10.6891,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.98492911,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"10","issue":"2","first_page":"1","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10246","display_name":"Mobile Ad Hoc Networks","score":0.9991999864578247,"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/T10246","display_name":"Mobile Ad Hoc Networks","score":0.9991999864578247,"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":0.9986000061035156,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9983000159263611,"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":0.8679425716400146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5648018717765808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5206781625747681},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4942924976348877},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4928291141986847},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4262213110923767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4198579490184784},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.32448893785476685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8679425716400146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5648018717765808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5206781625747681},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4942924976348877},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4928291141986847},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4262213110923767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4198579490184784},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.32448893785476685}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2530535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2530535","pdf_url":null,"source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1459829671","display_name":null,"funder_award_id":"CNS-1254192 and CNS-0923586","funder_id":"https://openalex.org/F4320337388","funder_display_name":"Division of Computer and Network Systems"},{"id":"https://openalex.org/G8272111553","display_name":null,"funder_award_id":"CITRIS-SPF-81 and CITRIS-SPF-165","funder_id":"https://openalex.org/F4320310688","funder_display_name":"Center for Information Technology Research in the Interest of Society"}],"funders":[{"id":"https://openalex.org/F4320310688","display_name":"Center for Information Technology Research in the Interest of Society","ror":"https://ror.org/00zv0wd17"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W317521241","https://openalex.org/W1506806321","https://openalex.org/W1578706292","https://openalex.org/W1580242306","https://openalex.org/W1582880497","https://openalex.org/W1612069777","https://openalex.org/W1663973292","https://openalex.org/W1825077972","https://openalex.org/W1864938698","https://openalex.org/W1973695593","https://openalex.org/W2003801825","https://openalex.org/W2019610001","https://openalex.org/W2020937027","https://openalex.org/W2023783988","https://openalex.org/W2037928371","https://openalex.org/W2041248965","https://openalex.org/W2047282676","https://openalex.org/W2054057221","https://openalex.org/W2058632086","https://openalex.org/W2065939774","https://openalex.org/W2071582233","https://openalex.org/W2084625525","https://openalex.org/W2085093677","https://openalex.org/W2100255987","https://openalex.org/W2100617218","https://openalex.org/W2103662601","https://openalex.org/W2105710533","https://openalex.org/W2107401636","https://openalex.org/W2110360611","https://openalex.org/W2114089854","https://openalex.org/W2117122370","https://openalex.org/W2117441298","https://openalex.org/W2117520883","https://openalex.org/W2121255383","https://openalex.org/W2128815505","https://openalex.org/W2129691081","https://openalex.org/W2136016236","https://openalex.org/W2145417574","https://openalex.org/W2151185679","https://openalex.org/W2152431187","https://openalex.org/W2155212243","https://openalex.org/W2160343401","https://openalex.org/W2162053441","https://openalex.org/W2169458211","https://openalex.org/W2169854556","https://openalex.org/W2799002609","https://openalex.org/W4231159306","https://openalex.org/W4254234063"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2394466068","https://openalex.org/W1989494794","https://openalex.org/W2122031327","https://openalex.org/W1184238669","https://openalex.org/W3032901101","https://openalex.org/W4318612353","https://openalex.org/W4390939596","https://openalex.org/W4389829534"],"abstract_inverted_index":{"As":[0],"an":[1,233],"integral":[2],"part":[3],"of":[4,24,61,85,92,97,142,170,202,252],"reliable":[5],"communication":[6],"in":[7,102,222],"wireless":[8,25],"networks,":[9],"effective":[10],"link":[11,28,43,47,52,77,207,216],"estimation":[12,30],"is":[13,56,265],"essential":[14],"for":[15,94],"routing":[16],"protocols.":[17],"However,":[18],"due":[19],"to":[20,99,258],"the":[21,86,95,145,167,172,188,196,200,213,223,249,263],"dynamic":[22],"nature":[23],"channels,":[26],"accurate":[27],"quality":[29,48,78,208],"remains":[31],"a":[32,41,90,140,204,254],"challenging":[33],"task.":[34],"In":[35,260],"this":[36],"article,":[37],"we":[38,88,180],"propose":[39,89],"4C,":[40,203,246],"novel":[42],"estimator":[44],"that":[45,121,148,182,211,244],"applies":[46],"prediction":[49,111,119,209],"along":[50],"with":[51,191,238,245],"estimation.":[53],"Our":[54,137,236],"approach":[55],"data":[57,64,72,98],"driven":[58],"and":[59,68,80,114,133,144,158,165,178,225,240],"consists":[60],"three":[62,118,189],"steps:":[63],"collection,":[65],"offline":[66,110],"modeling,":[67],"online":[69,206],"prediction.":[70],"The":[71,106],"collection":[73],"step":[74,108,198],"involves":[75,199],"gathering":[76],"data,":[79,87],"based":[81],"on":[82],"our":[83,103,176,226],"analysis":[84,177],"set":[91],"guidelines":[93],"amount":[96],"be":[100],"collected":[101],"experimental":[104],"scenarios.":[105],"modeling":[107],"includes":[109],"model":[112],"training":[113],"selection.":[115],"We":[116,218],"present":[117],"models":[120,138,190],"utilize":[122],"different":[123],"machine":[124],"learning":[125],"methods,":[126],"namely,":[127],"naive":[128],"Bayes":[129],"classifier,":[130],"logistic":[131,183],"regression,":[132],"artificial":[134],"neural":[135],"networks.":[136],"take":[139],"combination":[141],"PRR":[143],"physical-layer":[146],"information,":[147],"is,":[149],"Received":[150],"Signal":[151],"Strength":[152],"Indicator":[153,161],"(RSSI),":[154],"Signal-to-Noise":[155],"Ratio":[156],"(SNR),":[157],"Link":[159],"Quality":[160],"(LQI)":[162],"as":[163,230,232],"input,":[164],"output":[166],"success":[168],"probability":[169],"delivering":[171,253],"next":[173],"packet.":[174],"From":[175],"experiments,":[179],"find":[181],"regression":[184],"works":[185],"well":[186,231],"among":[187],"small":[192],"computational":[193],"cost.":[194],"Finally,":[195],"third":[197],"implementation":[201],"receiver-initiated":[205],"module":[210],"computes":[212],"short":[214],"temporal":[215],"quality.":[217],"conducted":[219],"extensive":[220],"experiments":[221,242],"Motelab":[224],"local":[227],"indoor":[228],"testbeds,":[229],"outdoor":[234],"deployment.":[235],"results":[237],"single-":[239],"multiple-senders":[241],"show":[243],"CTP":[247],"improves":[248],"average":[250],"cost":[251],"packet":[255],"by":[256],"20%":[257],"30%.":[259],"some":[261],"cases,":[262],"improvement":[264],"larger":[266],"than":[267],"45%.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}