{"id":"https://openalex.org/W4285274114","doi":"https://doi.org/10.1109/tsc.2022.3184835","title":"Optimizing Energy Efficiency for Data Center via Parameterized Deep Reinforcement Learning","display_name":"Optimizing Energy Efficiency for Data Center via Parameterized Deep Reinforcement Learning","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4285274114","doi":"https://doi.org/10.1109/tsc.2022.3184835"},"language":"en","primary_location":{"id":"doi:10.1109/tsc.2022.3184835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2022.3184835","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","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/A5016656803","display_name":"Yongyi Ran","orcid":"https://orcid.org/0000-0002-3200-1409"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yongyi Ran","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-3200-1409","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020194895","display_name":"Han Hu","orcid":"https://orcid.org/0000-0001-7532-0496"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Hu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7532-0496","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041572550","display_name":"Yonggang Wen","orcid":"https://orcid.org/0000-0002-2751-5114"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yonggang Wen","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-2751-5114","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007633349","display_name":"Xin Zhou","orcid":"https://orcid.org/0000-0001-5405-9890"},"institutions":[{"id":"https://openalex.org/I41317344","display_name":"Jiangxi Science and Technology Normal University","ror":"https://ror.org/04r1zkp10","country_code":"CN","type":"education","lineage":["https://openalex.org/I41317344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhou","raw_affiliation_strings":["School of Communications and Electronics, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, China"],"raw_orcid":"https://orcid.org/0000-0001-5405-9890","affiliations":[{"raw_affiliation_string":"School of Communications and Electronics, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I41317344"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.0095,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.9889835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"16","issue":"2","first_page":"1310","last_page":"1323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9993000030517578,"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":0.9993000030517578,"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/T12238","display_name":"Green IT and Sustainability","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9879000186920166,"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":0.8281852006912231},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8124035000801086},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.6764614582061768},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.5829346179962158},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5209521055221558},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5013492107391357},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.4629918038845062},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.45697128772735596},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3990914821624756},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3491560220718384},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.30958929657936096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2743935286998749},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21896231174468994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8281852006912231},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8124035000801086},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.6764614582061768},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.5829346179962158},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5209521055221558},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5013492107391357},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.4629918038845062},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.45697128772735596},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3990914821624756},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3491560220718384},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.30958929657936096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2743935286998749},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21896231174468994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsc.2022.3184835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2022.3184835","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1865835052","display_name":"\u591a\u536b\u661f\u73af\u5883\u4e0b\u7684\u81ea\u5b66\u4e60\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u89e3\u8026\u7814\u7a76","funder_award_id":"61971457","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6986487888","display_name":null,"funder_award_id":"NRF2020NRF-CG001-027","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G8885344885","display_name":null,"funder_award_id":"62003067","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1965522053","https://openalex.org/W1978631822","https://openalex.org/W1995622843","https://openalex.org/W2045274643","https://openalex.org/W2045845608","https://openalex.org/W2053211348","https://openalex.org/W2055043902","https://openalex.org/W2106516181","https://openalex.org/W2145339207","https://openalex.org/W2167804282","https://openalex.org/W2245628559","https://openalex.org/W2256420211","https://openalex.org/W2327388626","https://openalex.org/W2409375804","https://openalex.org/W2555390784","https://openalex.org/W2587207633","https://openalex.org/W2610077734","https://openalex.org/W2615330612","https://openalex.org/W2777549886","https://openalex.org/W2788426470","https://openalex.org/W2790037750","https://openalex.org/W2802106953","https://openalex.org/W2888655287","https://openalex.org/W2897417898","https://openalex.org/W2916308079","https://openalex.org/W2964229770","https://openalex.org/W2971974314","https://openalex.org/W2973229164","https://openalex.org/W2982560534","https://openalex.org/W2982619481","https://openalex.org/W2982625995","https://openalex.org/W2983710998","https://openalex.org/W2987965537","https://openalex.org/W4251091605","https://openalex.org/W6754447547","https://openalex.org/W6755326576"],"related_works":["https://openalex.org/W2051058708","https://openalex.org/W1494268238","https://openalex.org/W154868527","https://openalex.org/W1983207144","https://openalex.org/W2490706771","https://openalex.org/W2480116122","https://openalex.org/W2165967062","https://openalex.org/W4389065284","https://openalex.org/W2903994135","https://openalex.org/W2185314374"],"abstract_inverted_index":{"The":[0,26],"rapid":[1],"advancements":[2],"in":[3,18,125,209],"cloud":[4],"computing,":[5],"Big":[6],"Data":[7],"and":[8,73,116,121,129,135,148,167,176],"their":[9],"related":[10],"applications":[11],"have":[12],"led":[13],"to":[14,62,89,112,127,142,165,194],"a":[15,78,97,137],"skyrocketing":[16],"increase":[17],"data":[19,31,45],"center":[20,32],"energy":[21,33,65,169],"consumption":[22,66,170,213],"year":[23],"by":[24,214],"year.":[25],"prior":[27],"approaches":[28,179],"for":[29,102],"improving":[30],"efficiency":[34],"mostly":[35],"suffer":[36],"from":[37,67],"high":[38],"system":[39],"dynamics":[40,145],"or":[41],"the":[42,68,91,131,144,158,173,182,195,216],"complexity":[43],"of":[44,70,119,146,197,211],"centers.":[46],"In":[47,76],"this":[48],"paper,":[49],"we":[50],"propose":[51],"an":[52],"optimization":[53,178],"framework":[54],"based":[55,82,153],"on":[56],"deep":[57],"reinforcement":[58],"learning,":[59],"named":[60],"DeepEE,":[61,77],"jointly":[63],"optimize":[64],"perspectives":[69],"task":[71],"scheduling":[72],"cooling":[74,104,122,149,188],"control.":[75],"PArameterized":[79],"action":[80,93,218],"space":[81,94],"Deep":[83],"Q-Network":[84],"(PADQN)":[85],"algorithm":[86,161,185],"is":[87,107,140],"proposed":[88,132,159,183,202],"tackle":[90],"hybrid":[92],"problem.":[95],"Then,":[96],"dynamic":[98,187],"time":[99],"factor":[100],"mechanism":[101],"adjusting":[103],"control":[105,189],"interval":[106,190],"introduced":[108],"into":[109],"PADQN":[110,160],"(PADQN-D)":[111],"achieve":[113,204],"more":[114,205],"accurate":[115],"efficient":[117],"coordination":[118],"IT":[120,147,198],"subsystems.":[123,150],"Finally,":[124],"order":[126],"train":[128],"evaluate":[130],"algorithms":[133,203],"safely":[134],"quickly,":[136],"simulation":[138],"platform":[139],"built":[141],"model":[143],"Extensive":[151],"real-trace":[152],"experiments":[154],"illustrate":[155],"that:":[156],"1)":[157],"can":[162,191],"save":[163],"up":[164],"15%":[166],"10%":[168],"compared":[171],"with":[172,186],"baseline":[174],"siloed":[175],"joint":[177],"respectively;":[180],"2)":[181],"PADQN-D":[184],"better":[192],"adapt":[193],"change":[196],"workload;":[199],"3)":[200],"our":[201],"stable":[206],"performance":[207],"gain":[208],"terms":[210],"power":[212],"adopting":[215],"parameterized":[217],"space.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}