{"id":"https://openalex.org/W4367047246","doi":"https://doi.org/10.1145/3543507.3583436","title":"ELASTIC: Edge Workload Forecasting based on Collaborative Cloud-Edge Deep Learning","display_name":"ELASTIC: Edge Workload Forecasting based on Collaborative Cloud-Edge Deep Learning","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367047246","doi":"https://doi.org/10.1145/3543507.3583436"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583436","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","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/A5078439542","display_name":"Yanan Li","orcid":"https://orcid.org/0000-0003-4490-3466"},"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":"Yanan Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-4490-3466","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002395365","display_name":"Haitao Yuan","orcid":"https://orcid.org/0000-0001-6721-065X"},"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":"Haitao Yuan","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-6721-065X","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067123930","display_name":"Zhe Fu","orcid":"https://orcid.org/0000-0002-4637-6332"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Fu","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":"https://orcid.org/0000-0002-4637-6332","affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027148228","display_name":"Xiao Ma","orcid":"https://orcid.org/0000-0001-5742-8890"},"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":"Xiao Ma","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0001-5742-8890","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089690212","display_name":"Mengwei Xu","orcid":"https://orcid.org/0000-0001-6271-6993"},"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":"Mengwei Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0001-6271-6993","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054814598","display_name":"Shangguang Wang","orcid":"https://orcid.org/0000-0001-7245-1298"},"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":"Shangguang Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0001-7245-1298","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3056","last_page":"3066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9520000219345093,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.791115403175354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7100247144699097},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.7058380842208862},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.6578257083892822},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5798770189285278},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47265520691871643},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40430116653442383},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10363471508026123}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.791115403175354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7100247144699097},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.7058380842208862},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.6578257083892822},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5798770189285278},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47265520691871643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40430116653442383},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10363471508026123}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543507.3583436","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6899999976158142}],"awards":[{"id":"https://openalex.org/G560680150","display_name":null,"funder_award_id":"Z211100002121118","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"}],"funders":[{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2036455044","https://openalex.org/W2128160875","https://openalex.org/W2130942839","https://openalex.org/W2346747324","https://openalex.org/W2565330852","https://openalex.org/W2761694748","https://openalex.org/W2764100055","https://openalex.org/W2903871660","https://openalex.org/W2907492528","https://openalex.org/W2915609635","https://openalex.org/W2920031528","https://openalex.org/W2949003697","https://openalex.org/W2954358107","https://openalex.org/W2980856918","https://openalex.org/W2981559576","https://openalex.org/W2996361803","https://openalex.org/W2999301586","https://openalex.org/W3012562343","https://openalex.org/W3014839250","https://openalex.org/W3044011738","https://openalex.org/W3047401492","https://openalex.org/W3083668579","https://openalex.org/W3111143449","https://openalex.org/W3132522414","https://openalex.org/W3153345798","https://openalex.org/W3156287058","https://openalex.org/W3156564332","https://openalex.org/W3175016653","https://openalex.org/W3177318507","https://openalex.org/W3209727316","https://openalex.org/W4224314467","https://openalex.org/W4281388323","https://openalex.org/W6679436768","https://openalex.org/W6784415279"],"related_works":["https://openalex.org/W2000785801","https://openalex.org/W986318368","https://openalex.org/W2384410913","https://openalex.org/W2547038763","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2914646191","https://openalex.org/W4386004629","https://openalex.org/W3023564924","https://openalex.org/W2942586735"],"abstract_inverted_index":{"With":[0,71],"the":[1,8,17,24,60,72,101,119,134,139,144,154,162],"rapid":[2],"development":[3],"of":[4,23,46,75],"edge":[5,25,30,35,76,111,130,169,176],"computing":[6],"in":[7,90],"post-COVID19":[9],"pandemic":[10],"period,":[11],"precise":[12],"workload":[13,47,91,112,170],"forecasting":[14,48,113],"is":[15,82,100],"considered":[16],"basis":[18],"for":[19,110],"making":[20],"full":[21],"use":[22],"limited":[26],"resources,":[27],"and":[28,34,63,88,157,188],"both":[29,86,153],"service":[31,36,177],"providers":[32],"(ESPs)":[33],"consumers":[37],"(ESCs)":[38],"can":[39],"benefit":[40],"significantly":[41],"from":[42,66,173],"it.":[43],"Existing":[44],"paradigms":[45],"(i.e.,":[49],"edge-only":[50],"or":[51],"cloud-only)":[52],"are":[53],"improper,":[54],"due":[55],"to":[56,58,84,132,160],"failing":[57],"consider":[59],"inter-site":[61,140,158],"correlations":[62],"might":[64],"suffer":[65],"significant":[67],"data":[68],"transmission":[69],"delays.":[70],"increasing":[73],"adoption":[74],"platforms":[77],"by":[78],"web":[79],"services,":[80],"it":[81],"critical":[83],"balance":[85],"accuracy":[87],"efficiency":[89],"forecasting.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96,122,147],"propose":[97],"ELASTIC,":[98],"which":[99],"first":[102],"study":[103],"that":[104,180],"leverages":[105],"a":[106,124,149],"cloud-edge":[107],"collaborative":[108],"paradigm":[109],"with":[114],"multi-view":[115],"graphs.":[116],"Specifically,":[117],"at":[118,143],"global":[120],"stage,":[121,146],"design":[123,148],"learnable":[125],"aggregation":[126],"layer":[127,151],"on":[128,167],"each":[129],"site":[131],"reduce":[133],"time":[135,186],"consumption":[136],"while":[137],"capturing":[138],"correlation.":[141],"Additionally,":[142],"local":[145],"disaggregation":[150],"combining":[152],"intra-site":[155],"correlation":[156,159],"improve":[161],"prediction":[163],"accuracy.":[164],"Extensive":[165],"experiments":[166],"realistic":[168],"datasets":[171],"collected":[172],"China\u2019s":[174],"largest":[175],"provider":[178],"show":[179],"ELASTIC":[181],"outperforms":[182],"state-of-the-art":[183],"methods,":[184],"decreases":[185],"consumption,":[187],"reduces":[189],"communication":[190],"cost.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}