{"id":"https://openalex.org/W4391093891","doi":"https://doi.org/10.1109/bigdata59044.2023.10386549","title":"Deep Reinforcement Learning based Data Placement optimization in Data Center Networks","display_name":"Deep Reinforcement Learning based Data Placement optimization in Data Center Networks","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391093891","doi":"https://doi.org/10.1109/bigdata59044.2023.10386549"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","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/A5104232325","display_name":"Ravi Kaler","orcid":null},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ravi Kaler","raw_affiliation_strings":["Indian Institute of Technology,Computer Science & Engineering,Roorkee,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Computer Science & Engineering,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082753354","display_name":"Durga Toshniwal","orcid":null},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Durga Toshniwal","raw_affiliation_strings":["Indian Institute of Technology,Computer Science & Engineering,Roorkee,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Computer Science & Engineering,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104232325"],"corresponding_institution_ids":["https://openalex.org/I154851008"],"apc_list":null,"apc_paid":null,"fwci":0.9163,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82153211,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2293","last_page":"2302"},"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":0.9987999796867371,"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":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8603911399841309},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8003326058387756},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6951715350151062},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5602933168411255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44874992966651917},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.43992874026298523},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4182218611240387},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.40863990783691406},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3944239616394043},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.30369874835014343},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20126980543136597}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8603911399841309},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8003326058387756},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6951715350151062},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5602933168411255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44874992966651917},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.43992874026298523},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4182218611240387},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40863990783691406},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3944239616394043},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.30369874835014343},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20126980543136597},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1502450072","https://openalex.org/W1914389844","https://openalex.org/W1985680508","https://openalex.org/W2002227246","https://openalex.org/W2060311671","https://openalex.org/W2114296561","https://openalex.org/W2132479554","https://openalex.org/W2198756567","https://openalex.org/W2201220957","https://openalex.org/W2343550300","https://openalex.org/W2402305308","https://openalex.org/W2625108112","https://openalex.org/W2755080871","https://openalex.org/W2793843900","https://openalex.org/W2913002880","https://openalex.org/W2967703077","https://openalex.org/W2972669265","https://openalex.org/W2999590865","https://openalex.org/W3006402871","https://openalex.org/W3016938688","https://openalex.org/W3024916681","https://openalex.org/W3028340924","https://openalex.org/W3080781337","https://openalex.org/W3203597739","https://openalex.org/W3216082031","https://openalex.org/W4210291153","https://openalex.org/W4214717370","https://openalex.org/W6629901665"],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W3096874164","https://openalex.org/W1985560493","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2145363145","https://openalex.org/W1626977535","https://openalex.org/W2341346307","https://openalex.org/W3168977894","https://openalex.org/W2886166997"],"abstract_inverted_index":{"Intelligent":[0],"data":[1,4,9,18,30,43,49,112,124,202],"placement":[2,31,52,125,203],"in":[3,53,194,204],"center":[5],"networks":[6],"for":[7,178],"big":[8],"applications":[10],"is":[11,56,81,144],"a":[12,92,121,141],"constructive":[13],"approach":[14,126,177],"to":[15,68,146],"reduce":[16],"the":[17,25,36,39,54,62,108,169,175,191,197],"movement":[19,113],"delay,":[20],"which":[21],"can":[22],"further":[23],"improve":[24],"user":[26,75,181],"service":[27,115,182],"latency.":[28,116,183],"Traditionally,":[29],"methods":[32],"have":[33],"relied":[34],"on":[35,99,162],"study":[37],"of":[38,42,174,196],"prior":[40],"distribution":[41],"requests":[44,76],"discovered":[45],"via":[46],"network":[47,55,72],"trace":[48],"analysis.":[50],"Data":[51],"an":[57,83],"online":[58],"decision-making":[59],"problem.":[60],"Despite":[61],"available":[63],"machine":[64],"learning":[65,102],"architectures,":[66],"how":[67],"deal":[69],"with":[70,111],"dynamic":[71],"conditions":[73],"and":[74,114,136,152,159,171],"that":[77,104,127,187],"vary":[78],"over":[79],"time":[80],"still":[82],"unanswered":[84],"question.":[85],"Toward":[86],"this":[87,89],"goal,":[88],"research":[90],"formulates":[91],"Markov":[93],"Decision":[94],"Process":[95],"(MDP)":[96],"model":[97,189],"based":[98],"deep":[100],"reinforcement":[101],"(RL)":[103],"takes":[105],"into":[106],"account":[107],"delay":[109],"associated":[110],"The":[117,184],"proposed":[118,176],"method":[119],"presents":[120],"novel":[122],"intelligent":[123],"leverages":[128],"two":[129],"state-of-the-art":[130],"RL":[131],"techniques;":[132],"Deep":[133],"Q-Network":[134],"(DQN)":[135],"Soft":[137],"Actor-Critic":[138],"(SAC).":[139],"Additionally,":[140],"prioritized":[142],"butter":[143],"incorporated":[145],"replay":[147],"important":[148],"transitions":[149],"more":[150,155],"frequently":[151],"therefore,":[153],"learn":[154],"efficiently.":[156],"Extensive":[157],"experiments":[158],"analyses":[160],"conducted":[161],"Microsoft":[163],"Research":[164],"Cambridge":[165],"(MSR)":[166],"traces":[167],"show":[168],"effectiveness":[170],"superior":[172],"performance":[173],"minimizing":[179],"overall":[180,198],"results":[185],"highlight":[186],"our":[188],"outperforms":[190],"existing":[192],"techniques":[193],"terms":[195],"reward,":[199],"achieving":[200],"optimal":[201],"real-world":[205],"scenarios.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}