{"id":"https://openalex.org/W2953759293","doi":"https://doi.org/10.14778/3372716.3372722","title":"Planting trees for scalable and efficient canonical hub labeling","display_name":"Planting trees for scalable and efficient canonical hub labeling","publication_year":2019,"publication_date":"2019-12-09","ids":{"openalex":"https://openalex.org/W2953759293","doi":"https://doi.org/10.14778/3372716.3372722","mag":"2953759293"},"language":"en","primary_location":{"id":"doi:10.14778/3372716.3372722","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3372716.3372722","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.00140","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kartik Lakhotia","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kartik Lakhotia","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rajgopal Kannan","orcid":null},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajgopal Kannan","raw_affiliation_strings":["U.S Army Research Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"U.S Army Research Lab","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qing Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Dong","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":null,"display_name":"Viktor Prasanna","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viktor Prasanna","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5084,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.68976648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"13","issue":"4","first_page":"492","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.6133000254631042,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.6133000254631042,"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/T11106","display_name":"Data Management and Algorithms","score":0.23899999260902405,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12541","display_name":"Graph Labeling and Dimension Problems","score":0.07320000231266022,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/scalability","display_name":"Scalability","score":0.7875999808311462},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6868000030517578},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.47360000014305115},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43130001425743103},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.423799991607666},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.40610000491142273},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4025999903678894}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7875999808311462},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7401999831199646},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6868000030517578},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.47360000014305115},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4645000100135803},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.423799991607666},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.40610000491142273},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4058000147342682},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3691999912261963},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C207024777","wikidata":"https://www.wikidata.org/wiki/Q621673","display_name":"Search tree","level":3,"score":0.334199994802475},{"id":"https://openalex.org/C120373497","wikidata":"https://www.wikidata.org/wiki/Q1087987","display_name":"Parallel algorithm","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3372716.3372722","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3372716.3372722","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1907.00140","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.00140","pdf_url":"https://arxiv.org/pdf/1907.00140","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.00140","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.00140","pdf_url":"https://arxiv.org/pdf/1907.00140","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W85521454","https://openalex.org/W131619556","https://openalex.org/W1671906456","https://openalex.org/W1969483458","https://openalex.org/W1969678589","https://openalex.org/W1984336731","https://openalex.org/W1994924587","https://openalex.org/W2005945380","https://openalex.org/W2020880764","https://openalex.org/W2034102265","https://openalex.org/W2041172083","https://openalex.org/W2046526098","https://openalex.org/W2047998870","https://openalex.org/W2116437000","https://openalex.org/W2130747448","https://openalex.org/W2146583842","https://openalex.org/W2150418461","https://openalex.org/W2152776677","https://openalex.org/W2153204928","https://openalex.org/W2153280946","https://openalex.org/W2154768509","https://openalex.org/W2170616854","https://openalex.org/W2194288565","https://openalex.org/W2257437291","https://openalex.org/W2432978112","https://openalex.org/W2444127451","https://openalex.org/W2570742989","https://openalex.org/W2589167841","https://openalex.org/W2739409954","https://openalex.org/W2764587448","https://openalex.org/W2769133055","https://openalex.org/W2914774799","https://openalex.org/W2948227434","https://openalex.org/W2964092925","https://openalex.org/W4237536814","https://openalex.org/W4246342895","https://openalex.org/W4255388013","https://openalex.org/W6903379116"],"related_works":[],"abstract_inverted_index":{"Hub":[0,85],"labeling":[1,143,177,207],"is":[2,33,124,167,179,189],"widely":[3],"used":[4],"to":[5,49,67,127,169,181,218,227],"improve":[6],"the":[7,26,52,81,102,117,125,182,213,219],"latency":[8],"and":[9,65,89,96,144,205],"throughput":[10],"of":[11,119,137,209],"Point-to-Point":[12],"Shortest":[13],"Distance":[14],"(PPSD)":[15],"queries":[16],"in":[17,93],"graph":[18],"databases.":[19],"However,":[20],"constructing":[21],"hub":[22],"labeling,":[23],"even":[24],"via":[25],"state-of-the-art":[27,183,214],"Pruned":[28],"Landmark":[29],"Labeling":[30,86],"(PLL)":[31],"algorithm":[32,166],"computationally":[34],"intensive.":[35],"PLL":[36],"further":[37],"has":[38],"a":[39,94,129,138,155,159,231],"sequential":[40,173],"root":[41],"order":[42],"label":[43,60,111,131,187],"dependency":[44],"that":[45,79,113],"makes":[46],"it":[47,224],"challenging":[48],"parallelize.":[50],"Hence,":[51],"existing":[53],"parallel":[54,91,108,145,197,222],"approaches":[55],"are":[56],"often":[57],"plagued":[58],"by":[59],"size":[61,188],"increase,":[62],"poor":[63],"scalability":[64],"inability":[66],"process":[68,201],"large":[69],"weighted":[70],"graphs.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75],"develop":[76],"novel":[77],"algorithms":[78],"construct":[80,206],"minimal":[82],"(guaranteed)":[83],"Canonical":[84],"on":[87,147,154,192,230],"shared":[88],"distributed-memory":[90],"systems":[92],"scalable":[95],"efficient":[97],"manner.":[98],"Our":[99,122],"key":[100],"contribution,":[101],"PLaNT":[103,194],"algorithm,":[104,223],"provides":[105],"an":[106],"embarrassingly":[107],"approach":[109,123],"for":[110,140],"construction":[112],"scales":[114],"well":[115],"beyond":[116],"limits":[118],"current":[120],"practice.":[121],"first":[126],"employ":[128],"collaborative":[130],"partitioning":[132],"scheme":[133],"across":[134],"multiple":[135],"nodes":[136],"cluster,":[139],"completely":[141],"in-memory":[142],"querying":[146],"massive":[148],"graphs":[149,204],"whose":[150],"labels":[151],"cannot":[152],"fit":[153],"single":[156,160],"node.":[157],"On":[158],"node":[161,233],"with":[162],"72-threads,":[163],"our":[164,176,186],"shared-memory":[165,184,221],"up":[168,226],"47.4X":[170],"faster":[171,211],"than":[172,212],"PLL.":[174],"While":[175],"time":[178],"comparable":[180],"paraPLL,":[185],"17%":[190],"smaller":[191],"average.":[193],"demonstrates":[195],"superior":[196],"scalability.":[198],"It":[199],"can":[200],"significantly":[202],"larger":[203],"orders":[208],"magnitude":[210],"distributed":[215],"paraPLL.":[216],"Compared":[217],"best":[220],"achieves":[225],"9.5X":[228],"speedup":[229],"64":[232],"cluster.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2019-07-12T00:00:00"}