{"id":"https://openalex.org/W3159130076","doi":"https://doi.org/10.1109/icc.2016.7510682","title":"A prediction approach for correlated failures in distributed computing systems","display_name":"A prediction approach for correlated failures in distributed computing systems","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W3159130076","doi":"https://doi.org/10.1109/icc.2016.7510682","mag":"3159130076"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2016.7510682","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2016.7510682","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-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/A5101903639","display_name":"Weiwei Zheng","orcid":"https://orcid.org/0000-0002-8743-4017"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiwei Zheng","raw_affiliation_strings":["State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101832845","display_name":"Zhili Wang","orcid":"https://orcid.org/0000-0002-1667-3360"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhili Wang","raw_affiliation_strings":["State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082139392","display_name":"Haoqiu Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqiu Huang","raw_affiliation_strings":["State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100746917","display_name":"Luoming Meng","orcid":"https://orcid.org/0000-0002-1896-3230"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luoming Meng","raw_affiliation_strings":["State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042944721","display_name":"Xuesong Qiu","orcid":"https://orcid.org/0000-0002-7899-539X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Qiu","raw_affiliation_strings":["State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101903639"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.5791,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75430217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.998199999332428,"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/T12127","display_name":"Software System Performance and Reliability","score":0.998199999332428,"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/T12034","display_name":"Digital and Cyber Forensics","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7628062963485718},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7038232684135437},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6212673783302307},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5356893539428711},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5356438159942627},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.45339256525039673},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.415844202041626},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3514019250869751},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28412926197052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25742220878601074},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09126207232475281}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628062963485718},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7038232684135437},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6212673783302307},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5356893539428711},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5356438159942627},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.45339256525039673},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.415844202041626},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3514019250869751},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28412926197052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25742220878601074},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09126207232475281},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/icc.2016.7510682","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2016.7510682","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Communications (ICC)","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":42,"referenced_works":["https://openalex.org/W94959834","https://openalex.org/W183244809","https://openalex.org/W1558516248","https://openalex.org/W1775201033","https://openalex.org/W1969240345","https://openalex.org/W1970440495","https://openalex.org/W1998957169","https://openalex.org/W2002256242","https://openalex.org/W2008872214","https://openalex.org/W2011619454","https://openalex.org/W2020315857","https://openalex.org/W2022108140","https://openalex.org/W2022284665","https://openalex.org/W2028710551","https://openalex.org/W2058972361","https://openalex.org/W2078469142","https://openalex.org/W2094972030","https://openalex.org/W2103759606","https://openalex.org/W2106938068","https://openalex.org/W2111038504","https://openalex.org/W2114739461","https://openalex.org/W2116752428","https://openalex.org/W2122122011","https://openalex.org/W2142812297","https://openalex.org/W2148508494","https://openalex.org/W2151275011","https://openalex.org/W2153906066","https://openalex.org/W2158907675","https://openalex.org/W2163692925","https://openalex.org/W2164463086","https://openalex.org/W2173213060","https://openalex.org/W2287527836","https://openalex.org/W2288519351","https://openalex.org/W2289010250","https://openalex.org/W2303287830","https://openalex.org/W2343650655","https://openalex.org/W2394798516","https://openalex.org/W2404400579","https://openalex.org/W2751808730","https://openalex.org/W4285719527","https://openalex.org/W4300450738","https://openalex.org/W6603837692"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Failure":[0],"instances":[1,24],"in":[2,46,85,129,133],"distributed":[3],"computing":[4,43],"systems":[5],"(DCSs)":[6],"have":[7],"exhibited":[8],"temporal":[9],"and":[10,91,138,152],"spatial":[11],"correlations,":[12],"where":[13],"a":[14,20,29,64,86,103],"single":[15],"failure":[16,23,105,130],"instance":[17],"can":[18,154],"trigger":[19],"set":[21],"of":[22,42,55,74,97,112,135],"simultaneously":[25],"or":[26],"successively":[27],"within":[28],"short":[30],"time":[31],"interval.":[32],"We":[33],"investigate":[34],"an":[35,80],"effective":[36],"approach":[37,107,125],"to":[38,71,89,108],"predict":[39],"correlated":[40,75,104],"failures":[41,114],"elements":[44],"(CEs)":[45],"DCSs.":[47],"Correlated-failure":[48],"patterns":[49],"are":[50],"modeled":[51],"using":[52,95],"the":[53,110,116,123,148],"concept":[54],"probabilistic":[56],"shared":[57],"risk":[58],"groups":[59],"(PSRG).":[60],"Firstly,":[61],"we":[62,78,101],"design":[63],"new":[65],"structure":[66],"for":[67,157],"PSRG,":[68],"named":[69],"SPSRG,":[70],"describe":[72],"features":[73],"failures.":[76],"Then":[77],"exploit":[79],"association":[81],"rule":[82],"mining":[83],"technique":[84],"parallel":[87],"way":[88],"generate":[90],"update":[92],"our":[93],"SPSRG":[94],"information":[96],"CE-failure":[98],"states.":[99],"Finally,":[100],"propose":[102],"prediction":[106,131],"evaluate":[109],"probabilities":[111],"upcoming":[113],"from":[115],"SPSRG.":[117],"The":[118],"experimental":[119],"results":[120],"show":[121],"that":[122],"proposed":[124],"outperforms":[126],"other":[127],"approaches":[128],"performance":[132],"terms":[134],"precision,":[136],"recall":[137,153],"F-measure.":[139],"Moreover,":[140],"it":[141],"allows":[142],"employing":[143],"customizable":[144],"thresholds":[145],"by":[146],"which":[147],"trade-off":[149],"between":[150],"precision":[151],"be":[155],"adjusted":[156],"various":[158],"requirements.":[159]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}