{"id":"https://openalex.org/W2269220688","doi":"https://doi.org/10.1145/2788402.2788411","title":"Minimizing Interference and Maximizing Progress for Hadoop Virtual Machines","display_name":"Minimizing Interference and Maximizing Progress for Hadoop Virtual Machines","publication_year":2015,"publication_date":"2015-06-02","ids":{"openalex":"https://openalex.org/W2269220688","doi":"https://doi.org/10.1145/2788402.2788411","mag":"2269220688"},"language":"en","primary_location":{"id":"doi:10.1145/2788402.2788411","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2788402.2788411","pdf_url":null,"source":{"id":"https://openalex.org/S4210187660","display_name":"ACM SIGMETRICS Performance Evaluation Review","issn_l":"0163-5999","issn":["0163-5999","1557-9484"],"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 SIGMETRICS Performance Evaluation Review","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/A5053942348","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0003-3694-2246"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053527793","display_name":"Sundaresan Rajasekaran","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sundaresan Rajasekaran","raw_affiliation_strings":["The George Washington University, Washington, D.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The George Washington University, Washington, D.C","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075264696","display_name":"Shaohua Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaohua Duan","raw_affiliation_strings":["The George Washington University, Washington, D.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The George Washington University, Washington, D.C","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020963730","display_name":"Timothy Wood","orcid":"https://orcid.org/0000-0002-6728-4197"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Wood","raw_affiliation_strings":["The George Washington University, Washington, D.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The George Washington University, Washington, D.C","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034466328","display_name":"Mingfa Zhuy","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingfa Zhuy","raw_affiliation_strings":["The George Washington University, Washington, D.C"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The George Washington University, Washington, D.C","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.0703,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.97640251,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"42","issue":"4","first_page":"62","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":1.0,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9987999796867371,"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/T10714","display_name":"Software-Defined Networks and 5G","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/computer-science","display_name":"Computer science","score":0.8569177389144897},{"id":"https://openalex.org/keywords/virtualization","display_name":"Virtualization","score":0.6701865792274475},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6327990293502808},{"id":"https://openalex.org/keywords/virtual-machine","display_name":"Virtual machine","score":0.5956827402114868},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5257883071899414},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.510438859462738},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.5088655948638916},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.48190194368362427},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.47200843691825867},{"id":"https://openalex.org/keywords/spare-part","display_name":"Spare part","score":0.43989020586013794},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.4316239655017853},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.41900634765625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8569177389144897},{"id":"https://openalex.org/C513985346","wikidata":"https://www.wikidata.org/wiki/Q270471","display_name":"Virtualization","level":3,"score":0.6701865792274475},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6327990293502808},{"id":"https://openalex.org/C25344961","wikidata":"https://www.wikidata.org/wiki/Q192726","display_name":"Virtual machine","level":2,"score":0.5956827402114868},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5257883071899414},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.510438859462738},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5088655948638916},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.48190194368362427},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.47200843691825867},{"id":"https://openalex.org/C194648553","wikidata":"https://www.wikidata.org/wiki/Q1364774","display_name":"Spare part","level":2,"score":0.43989020586013794},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.4316239655017853},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.41900634765625},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2788402.2788411","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2788402.2788411","pdf_url":null,"source":{"id":"https://openalex.org/S4210187660","display_name":"ACM SIGMETRICS Performance Evaluation Review","issn_l":"0163-5999","issn":["0163-5999","1557-9484"],"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 SIGMETRICS Performance Evaluation Review","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W34718062","https://openalex.org/W185167974","https://openalex.org/W1523319063","https://openalex.org/W1820403722","https://openalex.org/W1984116073","https://openalex.org/W2017194553","https://openalex.org/W2022678927","https://openalex.org/W2040168785","https://openalex.org/W2045635963","https://openalex.org/W2048957547","https://openalex.org/W2058476250","https://openalex.org/W2070275167","https://openalex.org/W2085797995","https://openalex.org/W2096125134","https://openalex.org/W2098812784","https://openalex.org/W2102709380","https://openalex.org/W2107001003","https://openalex.org/W2107776555","https://openalex.org/W2128557401","https://openalex.org/W2145312209","https://openalex.org/W2157605676","https://openalex.org/W2169904482","https://openalex.org/W2173213060","https://openalex.org/W4235985402","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2055187606","https://openalex.org/W2088620127","https://openalex.org/W1969542292","https://openalex.org/W4214914670","https://openalex.org/W1498304890","https://openalex.org/W3006216828","https://openalex.org/W2084875360","https://openalex.org/W2904165227","https://openalex.org/W3123077549","https://openalex.org/W2743348030"],"abstract_inverted_index":{"Virtualization":[0],"promised":[1],"to":[2,32,70,89,118,122,134,143,160,199,210],"dramatically":[3],"increase":[4],"server":[5],"utilization":[6],"levels,":[7],"yet":[8],"many":[9],"data":[10,21,73,157],"centers":[11],"are":[12,23,149],"still":[13,173],"only":[14],"lightly":[15],"loaded.":[16],"In":[17,76],"some":[18],"ways,":[19],"big":[20,72],"applications":[22],"an":[24],"ideal":[25],"fit":[26],"for":[27,177],"using":[28,184],"this":[29,50,77],"residual":[30],"capacity":[31,65],"perform":[33],"meaningful":[34],"work,":[35],"but":[36],"the":[37,60,85,100,123,129,211],"high":[38,93],"level":[39],"of":[40,63,153],"interference":[41,91],"between":[42],"interactive":[43,95],"and":[44,97,131,172,186,188,221],"batch":[45,105],"processing":[46,106],"workloads":[47],"currently":[48],"prevents":[49],"from":[51],"being":[52],"a":[53,196],"practical":[54],"solution":[55],"in":[56,84,99],"virtualized":[57],"environments.":[58],"Further,":[59],"variable":[61],"nature":[62],"spare":[64],"may":[66],"make":[67],"it":[68],"difficult":[69],"meet":[71,108,144],"application":[74],"deadlines.":[75,112],"work":[78],"we":[79],"propose":[80],"two":[81],"schedulers:":[82],"one":[83,98],"virtualization":[86],"layer":[87],"designed":[88],"minimize":[90],"on":[92],"priority":[94],"services,":[96],"Hadoop":[101,120,165,219],"framework":[102],"that":[103,125,192],"helps":[104],"jobs":[107,166],"their":[109],"own":[110],"performance":[111,116,176],"Our":[113],"approach":[114],"uses":[115],"models":[117],"match":[119],"tasks":[121],"servers":[124],"will":[126],"benefit":[127],"them":[128],"most,":[130],"deadline-aware":[132],"scheduling":[133],"effectively":[135],"order":[136],"incoming":[137],"jobs.":[138],"We":[139,179],"use":[140],"admission":[141],"control":[142],"deadlines":[145,220],"even":[146],"when":[147],"resources":[148],"overloaded.":[150],"The":[151],"combination":[152],"these":[154],"schedulers":[155,194],"allows":[156],"center":[158],"administrators":[159],"safely":[161],"mix":[162],"resource":[163],"intensive":[164],"with":[167],"latency":[168],"sensitive":[169],"web":[170,201],"applications,":[171],"achieve":[174],"predictable":[175],"both.":[178],"have":[180],"implemented":[181],"our":[182,189,193],"system":[183],"Xen":[185,213],"Hadoop,":[187],"evaluation":[190],"shows":[191],"allow":[195],"mixed":[197],"cluster":[198],"reduce":[200],"response":[202],"times":[203,226],"by":[204,227],"more":[205,218],"than":[206],"ten":[207],"fold":[208],"compared":[209],"existing":[212],"Credit":[214],"Scheduler,":[215],"while":[216],"meeting":[217],"lowering":[222],"total":[223],"task":[224],"execution":[225],"6.5%.":[228]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
