{"id":"https://openalex.org/W2772687287","doi":"https://doi.org/10.1109/iiswc.2017.8167753","title":"Co-locating and concurrent fine-tuning MapReduce applications on microservers for energy efficiency","display_name":"Co-locating and concurrent fine-tuning MapReduce applications on microservers for energy efficiency","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2772687287","doi":"https://doi.org/10.1109/iiswc.2017.8167753","mag":"2772687287"},"language":"en","primary_location":{"id":"doi:10.1109/iiswc.2017.8167753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iiswc.2017.8167753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Symposium on Workload Characterization (IISWC)","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/A5010278061","display_name":"Maria Malik","orcid":"https://orcid.org/0000-0001-8425-2501"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maria Malik","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065583627","display_name":"Dean M. Tullsen","orcid":"https://orcid.org/0000-0003-3174-9316"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dean M. Tullsen","raw_affiliation_strings":["Department of Computer Science and Engineering, University of California, San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047382437","display_name":"Houman Homayoun","orcid":"https://orcid.org/0000-0001-8904-4699"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houman Homayoun","raw_affiliation_strings":["Department of Computer Science and Engineering, University of California, San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0789,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81175153,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9966999888420105,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9941999912261963,"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":0.8641778826713562},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.7141921520233154},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6936756372451782},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6192352175712585},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6177542805671692},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5708432793617249},{"id":"https://openalex.org/keywords/programming-paradigm","display_name":"Programming paradigm","score":0.43424081802368164},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"Fine-tuning","score":0.4198702573776245},{"id":"https://openalex.org/keywords/cost-efficiency","display_name":"Cost efficiency","score":0.418912798166275},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4104638695716858},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.27204251289367676}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8641778826713562},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.7141921520233154},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6936756372451782},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6192352175712585},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6177542805671692},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5708432793617249},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.43424081802368164},{"id":"https://openalex.org/C157524613","wikidata":"https://www.wikidata.org/wiki/Q2828883","display_name":"Fine-tuning","level":2,"score":0.4198702573776245},{"id":"https://openalex.org/C11644782","wikidata":"https://www.wikidata.org/wiki/Q15401790","display_name":"Cost efficiency","level":2,"score":0.418912798166275},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4104638695716858},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.27204251289367676},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iiswc.2017.8167753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iiswc.2017.8167753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Symposium on Workload Characterization (IISWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W35708471","https://openalex.org/W299741479","https://openalex.org/W1485435899","https://openalex.org/W1781794689","https://openalex.org/W1855098165","https://openalex.org/W1907782118","https://openalex.org/W1973578180","https://openalex.org/W1975912085","https://openalex.org/W1984244570","https://openalex.org/W1986800449","https://openalex.org/W1993209235","https://openalex.org/W2023214828","https://openalex.org/W2038361169","https://openalex.org/W2054153667","https://openalex.org/W2054604581","https://openalex.org/W2059290792","https://openalex.org/W2062611449","https://openalex.org/W2066443755","https://openalex.org/W2073987725","https://openalex.org/W2078994750","https://openalex.org/W2086291744","https://openalex.org/W2090330503","https://openalex.org/W2102709380","https://openalex.org/W2121788702","https://openalex.org/W2121884932","https://openalex.org/W2126584218","https://openalex.org/W2141181087","https://openalex.org/W2144509871","https://openalex.org/W2146434221","https://openalex.org/W2150139096","https://openalex.org/W2150478767","https://openalex.org/W2155072926","https://openalex.org/W2155396321","https://openalex.org/W2160121678","https://openalex.org/W2172339043","https://openalex.org/W2198342846","https://openalex.org/W2199558228","https://openalex.org/W2215849121","https://openalex.org/W2542189141","https://openalex.org/W2547552176","https://openalex.org/W2596562420","https://openalex.org/W2613215347","https://openalex.org/W3098310942","https://openalex.org/W3104065274","https://openalex.org/W3112651258","https://openalex.org/W4205941017","https://openalex.org/W4233484638","https://openalex.org/W4233517517","https://openalex.org/W4239385313","https://openalex.org/W4250180141","https://openalex.org/W4253824360","https://openalex.org/W6629143691","https://openalex.org/W6646312250","https://openalex.org/W6687403341","https://openalex.org/W6737210258"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4255224757","https://openalex.org/W2499527417","https://openalex.org/W3016452024"],"abstract_inverted_index":{"Datacenters":[0],"provide":[1],"flexibility":[2],"and":[3,8,21,31,59,72,86,99,115,183,213],"high":[4,15],"performance":[5,98],"for":[6,11,33,138,149,217],"users":[7],"cost":[9,58],"efficiency":[10,44],"operators.":[12],"However,":[13],"the":[14,43,48,69,81,84,88,105,127,168,190,202],"computational":[16],"demands":[17],"of":[18,45,65,83,97,192,221],"big":[19,34],"data":[20,35,49],"analytics":[22],"technologies":[23],"such":[24],"as":[25,111,113],"MapReduce,":[26],"a":[27,53,76,218],"dominant":[28],"programming":[29],"model":[30],"framework":[32],"analytics,":[36],"mean":[37],"that":[38,162,178],"even":[39],"small":[40],"changes":[41],"in":[42,47,79],"execution":[46],"center":[50],"can":[51],"have":[52],"large":[54],"effect":[55],"on":[56,206],"user":[57],"operational":[60,89],"cost.":[61,90],"Fine-tuning":[62],"configuration":[63,185],"parameters":[64,118,137,148,186],"MapReduce":[66,109,124,141,165,181,198],"applications":[67,125,142,166,182,199,211],"at":[68,126,167],"application,":[70],"architecture,":[71],"system":[73],"levels":[74],"plays":[75],"crucial":[77],"role":[78],"improving":[80,201],"energy-efficiency":[82,144],"server":[85],"reducing":[87],"In":[91,153],"this":[92,154],"work,":[93],"through":[94,179],"methodical":[95],"investigation":[96],"power":[100],"measurements,":[101],"we":[102,156],"demonstrate":[103],"how":[104,133],"interplay":[106],"among":[107],"various":[108],"configurations":[110],"well":[112],"application":[114,151],"architecture":[116],"level":[117,170],"create":[119],"new":[120],"opportunities":[121],"to":[122,146,171,196,209],"co-locate":[123],"node":[128,169],"level.":[129],"We":[130],"also":[131],"show":[132,177],"concurrently":[134],"fine-tuning":[135,147,184,210],"optimization":[136],"multiple":[139,164],"scheduled":[140],"improves":[143],"compared":[145,208],"each":[150],"separately.":[152],"paper,":[155],"present":[157],"Co-Located":[158],"Application":[159],"Optimization":[160],"(COLAO)":[161],"co-schedules":[163],"enhance":[172],"energy":[173],"efficiency.":[174],"Our":[175],"results":[176],"co-locating":[180],"concurrently,":[187],"COLAO":[188],"reduces":[189],"number":[191],"nodes":[193],"by":[194,204],"half":[195],"execute":[197],"while":[200],"EDP":[203],"2.2X":[205],"average,":[207],"individually":[212],"run":[214],"them":[215],"serially":[216],"broad":[219],"range":[220],"studied":[222],"workloads.":[223]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
