Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
<p dir="ltr">While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network...
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2019
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| الموضوعات: | |
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| _version_ | 1864513520341614592 |
|---|---|
| author | Muhammad Usama (3629090) |
| author2 | Junaid Qadir (16494902) Aunn Raza (16855545) Hunain Arif (16855548) Kok-lim Alvin Yau (16855551) Yehia Elkhatib (566867) Amir Hussain (783682) Ala Al-Fuqaha (4434340) |
| author2_role | author author author author author author author |
| author_facet | Muhammad Usama (3629090) Junaid Qadir (16494902) Aunn Raza (16855545) Hunain Arif (16855548) Kok-lim Alvin Yau (16855551) Yehia Elkhatib (566867) Amir Hussain (783682) Ala Al-Fuqaha (4434340) |
| author_role | author |
| dc.creator.none.fl_str_mv | Muhammad Usama (3629090) Junaid Qadir (16494902) Aunn Raza (16855545) Hunain Arif (16855548) Kok-lim Alvin Yau (16855551) Yehia Elkhatib (566867) Amir Hussain (783682) Ala Al-Fuqaha (4434340) |
| dc.date.none.fl_str_mv | 2019-05-14T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2019.2916648 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Unsupervised_Machine_Learning_for_Networking_Techniques_Applications_and_Research_Challenges/25425013 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Distributed computing and systems software Machine learning Unsupervised learning Deep learning Anomaly detection Internet of Things Quality of service Machine learning computer networks |
| dc.title.none.fl_str_mv | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The growing interest in applying unsupervised learning techniques in networking stems from their great success in other fields, such as computer vision, natural language processing, speech recognition, and optimal control (e.g., for developing autonomous self-driving cars). In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine learning. The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. We also provide a discussion on future directions and open research issues, while identifying potential pitfalls. While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature. Through this timely review, we aim to advance the current state of knowledge, by carefully synthesizing insights from previous survey papers, while providing contemporary coverage of the recent advances and innovations.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2019.2916648" target="_blank">https://dx.doi.org/10.1109/access.2019.2916648</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_30cf56e1052619a4e7829685af5a4308 |
| identifier_str_mv | 10.1109/access.2019.2916648 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25425013 |
| publishDate | 2019 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Unsupervised Machine Learning for Networking: Techniques, Applications and Research ChallengesMuhammad Usama (3629090)Junaid Qadir (16494902)Aunn Raza (16855545)Hunain Arif (16855548)Kok-lim Alvin Yau (16855551)Yehia Elkhatib (566867)Amir Hussain (783682)Ala Al-Fuqaha (4434340)Information and computing sciencesDistributed computing and systems softwareMachine learningUnsupervised learningDeep learningAnomaly detectionInternet of ThingsQuality of serviceMachine learningcomputer networks<p dir="ltr">While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The growing interest in applying unsupervised learning techniques in networking stems from their great success in other fields, such as computer vision, natural language processing, speech recognition, and optimal control (e.g., for developing autonomous self-driving cars). In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine learning. The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. We also provide a discussion on future directions and open research issues, while identifying potential pitfalls. While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature. Through this timely review, we aim to advance the current state of knowledge, by carefully synthesizing insights from previous survey papers, while providing contemporary coverage of the recent advances and innovations.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2019.2916648" target="_blank">https://dx.doi.org/10.1109/access.2019.2916648</a></p>2019-05-14T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2019.2916648https://figshare.com/articles/journal_contribution/Unsupervised_Machine_Learning_for_Networking_Techniques_Applications_and_Research_Challenges/25425013CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/254250132019-05-14T06:00:00Z |
| spellingShingle | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges Muhammad Usama (3629090) Information and computing sciences Distributed computing and systems software Machine learning Unsupervised learning Deep learning Anomaly detection Internet of Things Quality of service Machine learning computer networks |
| status_str | publishedVersion |
| title | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| title_full | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| title_fullStr | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| title_full_unstemmed | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| title_short | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| title_sort | Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges |
| topic | Information and computing sciences Distributed computing and systems software Machine learning Unsupervised learning Deep learning Anomaly detection Internet of Things Quality of service Machine learning computer networks |