Multimedia Data Flow Traffic Classification Using Intelligent Models Based on Traffic Patterns
Nowadays, there is high interest in modeling the type of multimedia traffic with the purpose of estimating the network resources required to guarantee the quality delivered to the user. In this work we propose a multimedia traffic classification model based on patterns that allows us to differentiat...
Saved in:
Published in | IEEE network Vol. 32; no. 6; pp. 100 - 107 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Nowadays, there is high interest in modeling the type of multimedia traffic with the purpose of estimating the network resources required to guarantee the quality delivered to the user. In this work we propose a multimedia traffic classification model based on patterns that allows us to differentiate the type of traffic by using video streaming and network characteristics as input parameters. We show that there is low correlation between network parameters and the delivered video quality. Because of this, in addition to network parameters, we also add video streaming parameters in order to improve the efficiency of our system. Finally, it should be noted that, based on the objective video quality received by the user, we have extracted traffic patterns that we use to perfor |
---|---|
AbstractList | Nowadays, there is high interest in modeling the type of multimedia traffic with the purpose of estimating the network resources required to guarantee the quality delivered to the user. In this work we propose a multimedia traffic classification model based on patterns that allows us to differentiate the type of traffic by using video streaming and network characteristics as input parameters. We show that there is low correlation between network parameters and the delivered video quality. Because of this, in addition to network parameters, we also add video streaming parameters in order to improve the efficiency of our system. Finally, it should be noted that, based on the objective video quality received by the user, we have extracted traffic patterns that we use to perfor |
Author | Canovas, Alejandro Jimenez, Jose Miguel Romero, Oscar Lloret, Jaime |
Author_xml | – sequence: 1 givenname: Alejandro surname: Canovas fullname: Canovas, Alejandro – sequence: 2 givenname: Jose Miguel surname: Jimenez fullname: Jimenez, Jose Miguel – sequence: 3 givenname: Oscar surname: Romero fullname: Romero, Oscar – sequence: 4 givenname: Jaime surname: Lloret fullname: Lloret, Jaime |
BookMark | eNo9kMFOAjEQhhuDiYA-gPHSxPNiZ7ut7VERlATUAySebLrbWVKy7OK2xPj2LgE9zRy-_5_JNyC9uqmRkGtgIwCm7xavk-UoZaBGoBiDFM5IH4RQCQj50SN9pjRLFMuyCzIIYdMhmeBpn3wu9lX0W3Te0icbLZ1WzTddtrYsfUHHlQ3Bd5uNvqnpKvh6TWd1xKrya6wjXTQOq0AfbUBHO-Iv-G5jxLYOl-S8tFXAq9McktV0shy_JPO359n4YZ4UnMuYiKJ7k-dcK1ZKDc4xdl9CbjOXo1ROp7zQLheOaYSiZJYpLIXMZA4aMyc0H5LbY--ubb72GKLZNPu27k6aFDLFmQR5oOBIFW0TQoul2bV-a9sfA8wcNJqDRnPQaE4au8zNMeMR8Z9XQnApU_4Ll49wQA |
CODEN | IENEET |
CitedBy_id | crossref_primary_10_1016_j_jnca_2019_102498 crossref_primary_10_1109_MCOM_101_2001126 crossref_primary_10_1109_MNET_011_1900514 crossref_primary_10_1109_ACCESS_2020_3006036 crossref_primary_10_1007_s12243_020_00770_7 crossref_primary_10_1155_2021_1825273 crossref_primary_10_1109_TMM_2019_2958764 |
Cites_doi | 10.1002/0471725293 10.1109/TIP.2003.819861 10.1109/ICNP.2012.6459963 10.1109/FPL.2010.22 10.1109/TIP.2010.2042111 10.1016/j.comcom.2014.03.026 10.1016/j.peva.2010.01.001 10.1109/JIOT.2017.2787959 10.1145/1064212.1064220 10.1145/1315245.1315286 10.1109/SURV.2008.080406 10.1016/j.measurement.2016.10.001 10.1016/j.phpro.2012.05.220 |
ContentType | Journal Article |
Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 |
Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 |
DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D |
DOI | 10.1109/MNET.2018.1800121 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
DatabaseTitleList | Technology Research Database |
Database_xml | – sequence: 1 dbid: RIE name: IEEE Xplore url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISSN | 1558-156X |
EndPage | 107 |
ExternalDocumentID | 10_1109_MNET_2018_1800121 8553662 |
Genre | orig-research |
GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 5VS 6IK 97E AAIKC AAJGR AAMNW AASAJ AAYOK ABQJQ ABVLG ACIWK AENEX AETIX AFOGA AI. AIBXA AKJIK ALLEH ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV AZLTO B-7 BEFXN BFFAM BGNUA BKEBE BKOMP BPEOZ CS3 DU5 EBS EJD F20 F5P HZ~ H~9 ICLAB IES IFIPE IFJZH IPLJI JAVBF LAI M43 MS~ O9- OCL PQQKQ RIA RIE RIG RNS TN5 VH1 XFK ZCA AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D |
ID | FETCH-LOGICAL-c336t-5c1563b3980f691dd007f1ba4dbe68d923c9db5d09e1cf0a08ef5646b19e4d593 |
IEDL.DBID | RIE |
ISSN | 0890-8044 |
IngestDate | Thu Oct 10 17:10:48 EDT 2024 Fri Aug 23 04:01:20 EDT 2024 Wed Jun 26 19:28:38 EDT 2024 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 6 |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c336t-5c1563b3980f691dd007f1ba4dbe68d923c9db5d09e1cf0a08ef5646b19e4d593 |
OpenAccessLink | https://riunet.upv.es/bitstream/10251/116174/2/Multimedia%20Data%20Flow%20Traffic%20Classification.pdf |
PQID | 2148306169 |
PQPubID | 36211 |
PageCount | 8 |
ParticipantIDs | ieee_primary_8553662 crossref_primary_10_1109_MNET_2018_1800121 proquest_journals_2148306169 |
PublicationCentury | 2000 |
PublicationDate | 2018-11-01 |
PublicationDateYYYYMMDD | 2018-11-01 |
PublicationDate_xml | – month: 11 year: 2018 text: 2018-11-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | New York |
PublicationPlace_xml | – name: New York |
PublicationTitle | IEEE network |
PublicationTitleAbbrev | NET-M |
PublicationYear | 2018 |
Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
References | ref13 ref12 ref15 ref14 kotevski (ref3) 0 ref11 ref10 ref2 ref8 ref7 ref9 ref4 ref6 ref5 symes (ref1) 2004 |
References_xml | – ident: ref5 doi: 10.1002/0471725293 – ident: ref2 doi: 10.1109/TIP.2003.819861 – start-page: 693 year: 0 ident: ref3 article-title: Performance Assessment of Metrics for Video Quality Estimation publication-title: Proc Conf Info Commun Energy Systems and Technologies contributor: fullname: kotevski – ident: ref7 doi: 10.1109/ICNP.2012.6459963 – ident: ref12 doi: 10.1109/FPL.2010.22 – ident: ref4 doi: 10.1109/TIP.2010.2042111 – ident: ref8 doi: 10.1016/j.comcom.2014.03.026 – year: 2004 ident: ref1 publication-title: Digital Video Compression contributor: fullname: symes – ident: ref11 doi: 10.1016/j.peva.2010.01.001 – ident: ref14 doi: 10.1109/JIOT.2017.2787959 – ident: ref10 doi: 10.1145/1064212.1064220 – ident: ref6 doi: 10.1145/1315245.1315286 – ident: ref9 doi: 10.1109/SURV.2008.080406 – ident: ref13 doi: 10.1016/j.measurement.2016.10.001 – ident: ref15 doi: 10.1016/j.phpro.2012.05.220 |
SSID | ssj0014532 |
Score | 2.3563137 |
Snippet | Nowadays, there is high interest in modeling the type of multimedia traffic with the purpose of estimating the network resources required to guarantee the... |
SourceID | proquest crossref ieee |
SourceType | Aggregation Database Publisher |
StartPage | 100 |
SubjectTerms | Classification Data mining Jitter Multimedia Multimedia communication Order parameters Packet loss Quality assessment Streaming media Telecommunication network management Telecommunication traffic Traffic control Traffic flow Traffic models Video data Video transmission |
Title | Multimedia Data Flow Traffic Classification Using Intelligent Models Based on Traffic Patterns |
URI | https://ieeexplore.ieee.org/document/8553662 https://www.proquest.com/docview/2148306169 |
Volume | 32 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV05T8MwFLZKJxi4CqJQkAcmRFInPrBHrqogtWJopU5E8bVQpYimQuLXYztpxDWwZXiOLH_OO_Le-x4A504vKkZzn1PnOiJM8shJcufIca5zzm0auDtHYzackscZnbXAZdMLY4wJxWcm9o8hl68XauV_lfU5pZh5hbvBUVr1ajUZA0LDMDLEfWs0IqTOYCZI9Efj-4kv4uJxwgOH2TcbFIaq_NLEwbwMdsBovbGqquQlXpUyVh8_OBv_u_NdsF37mfC6uhh7oGWKfbD1hX2wA55D821oHYF3eZnDwXzxDp3x8qwSMEzL9HVEAToYSgvgQ0PgWUI_RW2-hDfODGroJNYLnwJjZ7E8ANPB_eR2GNXjFiKFMSsjqlwshyUWHFkmEq2d-2ATmRMtDePaeYJKaEk1EiZRFuWIG0uZgzcRhmgq8CFoF4vCHAFo0ZVKjcaWEUFyzyGHnZ8mTUoM1RbzLrhYA5C9VqwaWYhGkMg8WplHK6vR6oKOP9BGsD7LLuitIcvq726ZpS66c0FQwsTx36tOwKZ_d9VN2APt8m1lTp1bUcqzcJ8-AUbBySs |
link.rule.ids | 315,786,790,802,27955,27956,55107 |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV07T8MwED5VZQAGXgVRKOCBCZHUqR-1Rx6tWmgrhlbqRJTEzkLVIpoKiV-P7SQVr4Etw1mx_Dn3yN19B3Bp9GLCWWRz6kJ5lMfCM5LCOHJCqEiItOW4O4cj3pvQhymbVuB63QujtXbFZ9q3jy6XrxbJyv4qawrGCLcKd8PYedzOu7XWOQPK3DgyLGxzNKa0yGEGWDaHo87YlnEJPxCOxeybFXJjVX7pYmdgurswLLeW15W8-Kss9pOPH6yN_937HuwUnia6ya_GPlT0_AC2v_AP1uDZtd-65hF0H2UR6s4W78iYL8srgdy8TFtJ5MBDrrgA9dcUnhmyc9RmS3RrDKFCRqJc-OQ4O-fLQ5h0O-O7nlcMXPASQnjmscREcyQmUuCUy0Ap40CkQRxRFWsulPEFE6liprDUQZLiCAudMm4ADqSmiklyBNX5Yq6PAaW4nbS0IimnkkaWRY4YTy3WLaqZSomow1UJQPia82qELh7BMrRohRatsECrDjV7oGvB4izr0CghC4svbxm2THxnwqCAy5O_V13AZm88HISD_ujxFLbse_LewgZUs7eVPjNORhafu7v1CQwbzH8 |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multimedia+Data+Flow+Traffic+Classification+Using+Intelligent+Models+Based+on+Traffic+Patterns&rft.jtitle=IEEE+network&rft.au=Canovas%2C+Alejandro&rft.au=Jimenez%2C+Jose+Miguel&rft.au=Romero%2C+Oscar&rft.au=Lloret%2C+Jaime&rft.date=2018-11-01&rft.pub=IEEE&rft.issn=0890-8044&rft.eissn=1558-156X&rft.volume=32&rft.issue=6&rft.spage=100&rft.epage=107&rft_id=info:doi/10.1109%2FMNET.2018.1800121&rft.externalDocID=8553662 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0890-8044&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0890-8044&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0890-8044&client=summon |