{"id":"https://openalex.org/W3212415307","doi":"https://doi.org/10.1109/rtsi50628.2021.9597313","title":"Mobile Network Traffic Prediction Using High Order Markov Chains Trained At Multiple Granularity","display_name":"Mobile Network Traffic Prediction Using High Order Markov Chains Trained At Multiple Granularity","publication_year":2021,"publication_date":"2021-09-06","ids":{"openalex":"https://openalex.org/W3212415307","doi":"https://doi.org/10.1109/rtsi50628.2021.9597313","mag":"3212415307"},"language":"en","primary_location":{"id":"doi:10.1109/rtsi50628.2021.9597313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rtsi50628.2021.9597313","pdf_url":null,"source":{"id":"https://openalex.org/S4306498810","display_name":"2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)","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/A5016722141","display_name":"Idio Guarino","orcid":"https://orcid.org/0009-0002-6141-0188"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Idio Guarino","raw_affiliation_strings":["University of Napoli \u201cFederico II\u201d, Italy","University of Napoli \"Federico II\", Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \u201cFederico II\u201d, Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"University of Napoli \"Federico II\", Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026481672","display_name":"Alfredo Nascita","orcid":"https://orcid.org/0000-0002-7395-4222"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alfredo Nascita","raw_affiliation_strings":["University of Napoli \u201cFederico II\u201d, Italy","University of Napoli \"Federico II\", Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \u201cFederico II\u201d, Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"University of Napoli \"Federico II\", Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059880462","display_name":"Giuseppe Aceto","orcid":"https://orcid.org/0000-0002-4445-6259"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Aceto","raw_affiliation_strings":["University of Napoli \u201cFederico II\u201d, Italy","University of Napoli \"Federico II\", Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \u201cFederico II\u201d, Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"University of Napoli \"Federico II\", Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064292700","display_name":"Antonio Pescap\u00e8","orcid":"https://orcid.org/0000-0002-0221-7444"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Antonio Pescape","raw_affiliation_strings":["University of Napoli \"Federico II\", Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \"Federico II\", Italy","institution_ids":["https://openalex.org/I71267560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I71267560"],"apc_list":null,"apc_paid":null,"fwci":0.4396,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63484167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"394","last_page":"399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9970999956130981,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9965999722480774,"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":0.8297160863876343},{"id":"https://openalex.org/keywords/provisioning","display_name":"Provisioning","score":0.567385196685791},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.5127714276313782},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5115893483161926},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5088980197906494},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5067785382270813},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4815840721130371},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.4645839333534241},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.46185600757598877},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.45913559198379517},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.43799158930778503},{"id":"https://openalex.org/keywords/network-traffic-simulation","display_name":"Network traffic simulation","score":0.43331393599510193},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.41096752882003784},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3528537154197693},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.3055591285228729},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29056787490844727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8297160863876343},{"id":"https://openalex.org/C172191483","wikidata":"https://www.wikidata.org/wiki/Q1071806","display_name":"Provisioning","level":2,"score":0.567385196685791},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.5127714276313782},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5115893483161926},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5088980197906494},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5067785382270813},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4815840721130371},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.4645839333534241},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.46185600757598877},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.45913559198379517},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.43799158930778503},{"id":"https://openalex.org/C94168897","wikidata":"https://www.wikidata.org/wiki/Q574324","display_name":"Network traffic simulation","level":4,"score":0.43331393599510193},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.41096752882003784},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3528537154197693},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.3055591285228729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29056787490844727},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/rtsi50628.2021.9597313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rtsi50628.2021.9597313","pdf_url":null,"source":{"id":"https://openalex.org/S4306498810","display_name":"2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/1032213","is_oa":false,"landing_page_url":"https://hdl.handle.net/11585/1032213","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1975627592","https://openalex.org/W2022297269","https://openalex.org/W2077527312","https://openalex.org/W2080684559","https://openalex.org/W2097749765","https://openalex.org/W2107372872","https://openalex.org/W2304503150","https://openalex.org/W2324823555","https://openalex.org/W2591735613","https://openalex.org/W2775542991","https://openalex.org/W2968518053","https://openalex.org/W2982309555","https://openalex.org/W3002305579","https://openalex.org/W3127084347"],"related_works":["https://openalex.org/W2374980776","https://openalex.org/W2352713638","https://openalex.org/W2612734354","https://openalex.org/W2382692540","https://openalex.org/W2578585306","https://openalex.org/W2138225277","https://openalex.org/W4242927786","https://openalex.org/W2924962435","https://openalex.org/W4379534844","https://openalex.org/W2745966507"],"abstract_inverted_index":{"Over":[0],"the":[1,3,30,45,54,133,138,154,158,163,183],"years,":[2],"need":[4,46,112],"for":[5,37],"communication":[6],"networks":[7],"capable":[8],"of":[9,14,27,29,57,65,72,135,157,165,175,185],"providing":[10],"an":[11,69,79],"ever-increasing":[12],"set":[13],"services":[15],"has":[16],"grown.":[17],"In":[18],"order":[19],"to":[20,48,52,61,93,113,131,141],"satisfy":[21],"user":[22],"requirements":[23],"and":[24,40,60,91,117,151,178],"provide":[25],"guarantees":[26],"reliability":[28],"network":[31,58,75,89,120],"itself,":[32],"efficient":[33],"techniques":[34],"are":[35],"required":[36],"analysis,":[38],"evaluation":[39],"design.":[41],"For":[42],"this":[43,106,124],"reason,":[44],"arises":[47],"have":[49,99],"models":[50,110,167,169],"able":[51],"represent":[53],"peculiar":[55],"characteristics":[56],"traffic":[59,76,146],"produce":[62],"reliable":[63],"predictions":[64],"its":[66],"behavior":[67],"in":[68,123],"adequate":[70],"period":[71],"time.":[73],"Therefore,":[74,122],"prediction":[77,155],"plays":[78],"important":[80],"role":[81],"by":[82,161],"supporting":[83],"many":[84],"practical":[85],"applications,":[86],"ranging":[87],"from":[88],"planning":[90],"provisioning":[92],"security.":[94],"Several":[95],"works":[96],"so":[97],"far":[98],"focused":[100],"on":[101,171,182],"building":[102],"app-specific":[103],"models.":[104],"However,":[105],"choice":[107],"produces":[108],"multiple":[109],"that":[111],"be":[114],"properly":[115],"managed":[116],"deployed":[118],"across":[119],"devices.":[121],"paper,":[125],"we":[126],"explore":[127],"different":[128],"training":[129],"strategies":[130],"reduce":[132],"number":[134],"models,":[136],"adopting":[137],"Markov":[139],"Chains":[140],"model":[142,180],"mobile":[143],"video":[144,176,187],"apps":[145,177],"at":[147],"packet-level.":[148],"We":[149],"discuss":[150],"experimentally":[152],"evaluate":[153],"effectiveness":[156],"proposed":[159],"approaches":[160],"comparing":[162],"performance":[164],"app":[166],"with":[168],"trained":[170,181],"a":[172,179],"specific":[173],"category":[174],"mix":[184],"all":[186],"traffic.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}