{"id":"https://openalex.org/W2159311877","doi":"https://doi.org/10.1109/hipc.2010.5713169","title":"Anomaly detection in large-scale coalition clusters for dependability assurance","display_name":"Anomaly detection in large-scale coalition clusters for dependability assurance","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W2159311877","doi":"https://doi.org/10.1109/hipc.2010.5713169","mag":"2159311877"},"language":"en","primary_location":{"id":"doi:10.1109/hipc.2010.5713169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hipc.2010.5713169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on High Performance Computing","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/A5102787759","display_name":"Qiang Guan","orcid":"https://orcid.org/0000-0002-3804-8945"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Guan","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108412614","display_name":"Derek T. Smith","orcid":"https://orcid.org/0009-0005-9158-8050"},"institutions":[{"id":"https://openalex.org/I207123951","display_name":"New Mexico Institute of Mining and Technology","ror":"https://ror.org/005p9kw61","country_code":"US","type":"education","lineage":["https://openalex.org/I207123951"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Smith","raw_affiliation_strings":["Department of Computer Science and Engineering, New Mexico Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New Mexico Technology, USA","institution_ids":["https://openalex.org/I207123951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082758762","display_name":"Song Fu","orcid":"https://orcid.org/0000-0002-7705-0829"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Fu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3623,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.82708071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.9993000030517578,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9884999990463257,"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/dependability","display_name":"Dependability","score":0.8073561191558838},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7934170961380005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7909798622131348},{"id":"https://openalex.org/keywords/troubleshooting","display_name":"Troubleshooting","score":0.6512123346328735},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6217730641365051},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5617741346359253},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5399250388145447},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4461190700531006},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42888057231903076},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.42463216185569763},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4126542806625366},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3655564486980438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20490485429763794},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12340274453163147}],"concepts":[{"id":"https://openalex.org/C77019957","wikidata":"https://www.wikidata.org/wiki/Q2689057","display_name":"Dependability","level":2,"score":0.8073561191558838},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7934170961380005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7909798622131348},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.6512123346328735},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6217730641365051},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5617741346359253},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5399250388145447},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4461190700531006},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42888057231903076},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.42463216185569763},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4126542806625366},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3655564486980438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20490485429763794},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12340274453163147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hipc.2010.5713169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hipc.2010.5713169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on High Performance Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.44999998807907104}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338304","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W259338706","https://openalex.org/W1558516248","https://openalex.org/W1560061049","https://openalex.org/W1817561967","https://openalex.org/W1904710828","https://openalex.org/W1963853421","https://openalex.org/W1965626898","https://openalex.org/W1984578990","https://openalex.org/W1985699615","https://openalex.org/W1990911977","https://openalex.org/W2000324328","https://openalex.org/W2025621112","https://openalex.org/W2039475678","https://openalex.org/W2096121981","https://openalex.org/W2099111195","https://openalex.org/W2103759606","https://openalex.org/W2105454049","https://openalex.org/W2107263349","https://openalex.org/W2118887058","https://openalex.org/W2122646361","https://openalex.org/W2123511529","https://openalex.org/W2138509363","https://openalex.org/W2140190241","https://openalex.org/W2143220335","https://openalex.org/W2147173510","https://openalex.org/W2147176980","https://openalex.org/W2148508494","https://openalex.org/W2155711867","https://openalex.org/W2157500273","https://openalex.org/W2158016161","https://openalex.org/W2158907675","https://openalex.org/W2160821994","https://openalex.org/W2161006788","https://openalex.org/W2171935755","https://openalex.org/W2405200838","https://openalex.org/W2473052521","https://openalex.org/W6633264363","https://openalex.org/W6639951305","https://openalex.org/W6646175012","https://openalex.org/W6677713607","https://openalex.org/W6680456895","https://openalex.org/W6680785567","https://openalex.org/W6681675132","https://openalex.org/W6685327664","https://openalex.org/W6713091605","https://openalex.org/W6720450004"],"related_works":["https://openalex.org/W3013479934","https://openalex.org/W4210597238","https://openalex.org/W4318325534","https://openalex.org/W4206476896","https://openalex.org/W4240398146","https://openalex.org/W2950310564","https://openalex.org/W4238338086","https://openalex.org/W2467308209","https://openalex.org/W2913357653","https://openalex.org/W1981753479"],"abstract_inverted_index":{"In":[0,77],"large-scale":[1],"high-performance":[2],"computing":[3],"systems,":[4],"component":[5],"failures":[6],"become":[7],"norms":[8],"instead":[9],"of":[10,62,94,97,103],"exceptions.":[11],"Failure":[12],"occurrence":[13],"as":[14,16],"well":[15],"its":[17],"impact":[18],"on":[19,149],"system":[20,32,104],"performance":[21],"and":[22,34,70,133,169],"operation":[23],"costs":[24],"are":[25,46,122,136],"becoming":[26],"an":[27,82],"increasingly":[28],"important":[29],"concern":[30],"to":[31,41,54,111,138],"designers":[33],"administrators.":[35],"When":[36],"a":[37,95,116,150],"compute":[38],"node":[39],"fails":[40],"function":[42],"properly,":[43],"health-related":[44],"data":[45,109,114,130],"valuable":[47],"for":[48,85],"troubleshooting.":[49],"However,":[50],"it":[51],"is":[52,68,92],"challenging":[53],"effectively":[55,162],"identify":[56,139],"anomalies":[57],"from":[58],"the":[59,129],"voluminous":[60],"amount":[61],"noisy,":[63],"high-dimensional":[64],"data.":[65,106],"Manual":[66],"detection":[67,87,135],"time-consuming":[69],"error-prone.":[71],"It":[72,91],"does":[73],"not":[74],"scale":[75],"well.":[76],"this":[78],"paper,":[79],"we":[80],"present":[81],"autonomic":[83],"mechanism":[84,160],"anomaly":[86],"in":[88,115],"coalition":[89],"clusters.":[90],"composed":[93],"set":[96],"techniques":[98],"that":[99,158],"facilitates":[100],"automatic":[101],"analysis":[102],"health":[105,113],"We":[107,144],"apply":[108],"transformation":[110],"format":[112],"uniform":[117],"manner.":[118],"Then":[119],"principal":[120],"variables":[121],"chosen":[123],"by":[124],"feature":[125],"selection,":[126],"which":[127],"reduces":[128],"size.":[131],"Clustering":[132],"outlier":[134],"explored":[137],"nodes":[140,165],"with":[141,166],"anomalous":[142],"behavior.":[143],"evaluate":[145],"our":[146,159],"prototype":[147],"implementation":[148],"production":[151],"institution-wide":[152],"computational":[153],"grid.":[154],"The":[155],"results":[156],"show":[157],"can":[161],"detect":[163],"faulty":[164],"high":[167],"accuracy":[168],"low":[170],"computation":[171],"overhead.":[172]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}