{"id":"https://openalex.org/W2688217289","doi":"https://doi.org/10.1109/icassp.2017.7953311","title":"Intelligent compressive data gathering using data ferries for wireless sensor networks","display_name":"Intelligent compressive data gathering using data ferries for wireless sensor networks","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2688217289","doi":"https://doi.org/10.1109/icassp.2017.7953311","mag":"2688217289"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7953311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5039694624","display_name":"Siwang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siwang Zhou","raw_affiliation_strings":["College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042912655","display_name":"Qian Zhong","orcid":"https://orcid.org/0000-0001-7651-7872"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Zhong","raw_affiliation_strings":["College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014386711","display_name":"Bo Ou","orcid":"https://orcid.org/0000-0001-6936-9955"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Ou","raw_affiliation_strings":["College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electrical Engineering, Hunan University, ChangSha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001033170","display_name":"Yonghe Liu","orcid":"https://orcid.org/0000-0003-2909-6088"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yonghe Liu","raw_affiliation_strings":["Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.438,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59787664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"6015","last_page":"6019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9983000159263611,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9980999827384949,"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/leverage","display_name":"Leverage (statistics)","score":0.789406418800354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768279910087585},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7354574203491211},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.5842007398605347},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.5587803721427917},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5356872081756592},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5286156535148621},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.5232976078987122},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.49088698625564575},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.487705796957016},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4655023217201233},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.41823622584342957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32722052931785583},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15793323516845703},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1354382038116455},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11310872435569763}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.789406418800354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768279910087585},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7354574203491211},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.5842007398605347},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.5587803721427917},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5356872081756592},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5286156535148621},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.5232976078987122},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.49088698625564575},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.487705796957016},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4655023217201233},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.41823622584342957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32722052931785583},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15793323516845703},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1354382038116455},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11310872435569763},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7953311","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":11,"referenced_works":["https://openalex.org/W1575713165","https://openalex.org/W1979257617","https://openalex.org/W1986931325","https://openalex.org/W2045385910","https://openalex.org/W2047064261","https://openalex.org/W2051747891","https://openalex.org/W2126644064","https://openalex.org/W2132438068","https://openalex.org/W2151131483","https://openalex.org/W2165742939","https://openalex.org/W2964014391"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W3081133439","https://openalex.org/W4386246791","https://openalex.org/W2945537679","https://openalex.org/W3211701140","https://openalex.org/W2952280724","https://openalex.org/W2133103607","https://openalex.org/W2296466480"],"abstract_inverted_index":{"The":[0,80],"latest":[1],"research":[2],"progress":[3],"of":[4,7,19,40,51,70,100,109,122],"the":[5,17,37,41,48,56,88,94,98,107,114,119,129,133,138],"theory":[6],"compressed":[8],"sensing":[9,42,102],"(CS)":[10],"over":[11],"graphs":[12],"makes":[13],"it":[14],"possible":[15],"that":[16,128],"advantage":[18],"CS":[20],"can":[21],"be":[22],"utilized":[23],"by":[24,117],"data":[25,29,43,52,58,66,110,115],"ferries":[26,111],"to":[27,45,137],"gather":[28],"in":[30],"WSNs.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,61],"leverage":[36],"non-uniform":[38],"distribution":[39,121],"field":[44],"significantly":[46],"reduce":[47],"required":[49],"number":[50,108],"ferries,":[53],"yet":[54],"ensuring":[55],"recovered":[57],"quality.":[59],"Specially,":[60],"propose":[62],"an":[63,71],"intelligent":[64],"compressive":[65],"gathering":[67],"scheme":[68,131],"consisting":[69],"efficient":[72],"stopping":[73,82],"criterion":[74,83],"and":[75],"a":[76],"novel":[77],"learning":[78,118],"strategy.":[79],"proposed":[81,130],"is":[84],"based":[85],"only":[86],"on":[87,93,97],"gathered":[89,123],"data,":[90],"without":[91],"relying":[92],"priori":[95],"knowledge":[96],"sparsity":[99],"unknown":[101],"data.":[103,124],"Our":[104],"strategy":[105],"minimizes":[106],"while":[112],"guaranteeing":[113],"quality":[116,135],"statistical":[120],"Simulation":[125],"results":[126],"show":[127],"improves":[132],"reconstruction":[134],"compared":[136],"existing":[139],"ones.":[140]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
