{"id":"https://openalex.org/W2746415818","doi":"https://doi.org/10.1145/3085576","title":"Energy-Efficient Collection of Sparse Data in Wireless Sensor Networks Using Sparse Random Matrices","display_name":"Energy-Efficient Collection of Sparse Data in Wireless Sensor Networks Using Sparse Random Matrices","publication_year":2017,"publication_date":"2017-08-16","ids":{"openalex":"https://openalex.org/W2746415818","doi":"https://doi.org/10.1145/3085576","mag":"2746415818"},"language":"en","primary_location":{"id":"doi:10.1145/3085576","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3085576","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/A5062939405","display_name":"Xiaohan Yu","orcid":"https://orcid.org/0000-0001-8448-6287"},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohan Yu","raw_affiliation_strings":["Zhejiang Gongshang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University, Hangzhou, China","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009631871","display_name":"Seung Jun Baek","orcid":"https://orcid.org/0000-0002-1226-0147"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung Jun Baek","raw_affiliation_strings":["Korea University, Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0002-1226-0147","affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4619,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.83495991,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"13","issue":"3","first_page":"1","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998999834060669,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9997000098228455,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.7616982460021973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7449423670768738},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5497109889984131},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.5171788930892944},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4894465506076813},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48551177978515625},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.45983001589775085},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.45454949140548706},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.44059619307518005},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.43053358793258667},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41791096329689026},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32959315180778503},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18294984102249146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16130205988883972}],"concepts":[{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.7616982460021973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7449423670768738},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5497109889984131},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.5171788930892944},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4894465506076813},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48551177978515625},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.45983001589775085},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.45454949140548706},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.44059619307518005},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.43053358793258667},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41791096329689026},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32959315180778503},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18294984102249146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16130205988883972},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3085576","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3085576","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":[{"score":0.9100000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W174362428","https://openalex.org/W340244495","https://openalex.org/W1425488884","https://openalex.org/W1971402995","https://openalex.org/W1986022261","https://openalex.org/W1988569331","https://openalex.org/W1990327548","https://openalex.org/W2006033216","https://openalex.org/W2011452458","https://openalex.org/W2030449718","https://openalex.org/W2036268493","https://openalex.org/W2044628510","https://openalex.org/W2053855589","https://openalex.org/W2066700938","https://openalex.org/W2068849277","https://openalex.org/W2076665288","https://openalex.org/W2081065314","https://openalex.org/W2102372792","https://openalex.org/W2102580993","https://openalex.org/W2104266187","https://openalex.org/W2111619626","https://openalex.org/W2115787343","https://openalex.org/W2119667497","https://openalex.org/W2123241700","https://openalex.org/W2125555950","https://openalex.org/W2128633079","https://openalex.org/W2129726418","https://openalex.org/W2130403046","https://openalex.org/W2136982937","https://openalex.org/W2141573624","https://openalex.org/W2159267513","https://openalex.org/W2165277891","https://openalex.org/W2171821354","https://openalex.org/W2196956961","https://openalex.org/W2202090419","https://openalex.org/W2296616510","https://openalex.org/W2614835259","https://openalex.org/W2963096952","https://openalex.org/W3145128584","https://openalex.org/W3151600927","https://openalex.org/W4250955649","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2737338842","https://openalex.org/W3005946484"],"abstract_inverted_index":{"We":[0,17,97,117,142],"consider":[1],"the":[2,24,44,53,56,74,83,88,92,115,145,157,165,173],"energy":[3,86],"efficiency":[4],"of":[5,41,87,122],"collecting":[6],"sparse":[7,20],"data":[8,51,64,93,123],"in":[9,163,171],"wireless":[10],"sensor":[11],"networks":[12],"using":[13],"compressive":[14],"sensing":[15,25],"(CS).":[16],"use":[18],"a":[19,37,63,108,120,131],"random":[21],"matrix":[22],"as":[23],"matrix,":[26],"which":[27],"we":[28,59],"call":[29],"Sparse":[30],"Random":[31],"Sampling":[32],"(SRS).":[33],"In":[34],"SRS,":[35],"only":[36,162],"randomly":[38],"selected":[39],"subset":[40],"nodes,":[42,46,58],"called":[43],"source":[45,57,79],"are":[47],"required":[48],"to":[49,52,61,112,134],"report":[50],"sink.":[54],"Given":[55],"intend":[60],"construct":[62,119],"gathering":[65,124],"tree":[66,89],"such":[67],"that":[68,100,144,156],"(1)":[69],"it":[70],"is":[71,95,103,148],"rooted":[72],"at":[73,139],"sink":[75],"and":[76,81,105,129,152],"spans":[77],"every":[78],"node":[80],"(2)":[82],"minimum":[84,166],"residual":[85,167],"nodes":[90],"after":[91],"collection":[94],"maximized.":[96],"first":[98],"show":[99,143,155],"this":[101],"problem":[102],"NP-complete":[104],"then":[106],"develop":[107],"polynomial":[109],"time":[110],"algorithm":[111,133,147,159],"approximately":[113],"solve":[114],"problem.":[116],"greedily":[118],"sequence":[121],"trees":[125],"over":[126],"multiple":[127],"rounds":[128],"propose":[130],"polynomial-time":[132],"collect":[135],"linearly":[136],"combined":[137],"measurements":[138],"each":[140],"round.":[141],"proposed":[146,158],"provably":[149],"near-optimal.":[150],"Simulation":[151],"experimental":[153],"results":[154],"excels":[160],"not":[161],"increasing":[164],"energy,":[168],"but":[169],"also":[170],"extending":[172],"network":[174],"lifetime.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
