Research on mobile network traffic taxonomy

A huge amount of mobile traffic runs on Internet every day. The complex mobile traffic data may degrade the network performance if they are not well managed. As the important foundation of network management, mobile network traffic classification aim to map IP packets into a predefined traffic class set. Most work in this area until now has focused on classification schemes. In contrast, little attention has been paid towards traffic class definition. Various kinds of traffic class lead to difficultly comparing these traffic classification methods. This paper presents a mobile traffic taxonomy based on ontology paradigm. Its meta-characteristic is the mobile traffic communication from users' perspective. It defines mobile network traffic into four levels of categories. And the taxonomy could be used for multiple traffic classification purposes.

[1]  Zhen Liu,et al.  Large traffic flows classification method , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[2]  Michalis Faloutsos,et al.  ProfileDroid: multi-layer profiling of android applications , 2012, Mobicom '12.

[3]  Shigehiro Ano,et al.  Traffic classification on mobile core network considering regularity of background traffic , 2015, 2015 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR).

[4]  Qiang Xu,et al.  Identifying diverse usage behaviors of smartphone apps , 2011, IMC '11.

[5]  Sonja Filiposka,et al.  Smartphone User’s Traffic Characteristics and Modelling , 2013 .

[6]  Toru Abe,et al.  Traffic Classification in Mobile IP Network , 2009, Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications.

[7]  Kensuke Fukuda,et al.  Towards a taxonomy of darknet traffic , 2014, 2014 International Wireless Communications and Mobile Computing Conference (IWCMC).

[8]  Yiqing Zhou,et al.  Maximum entropy based IP-traffic classification in mobile communication networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[9]  James Won-Ki Hong,et al.  Fine‐grained traffic classification based on functional separation , 2013, Int. J. Netw. Manag..

[10]  Fang Liu,et al.  Characterizing User Behavior in Mobile Internet , 2015, IEEE Transactions on Emerging Topics in Computing.

[11]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[12]  Yong Liao,et al.  SAMPLES: Self Adaptive Mining of Persistent LExical Snippets for Classifying Mobile Application Traffic , 2015, MobiCom.

[13]  Igor Santos,et al.  On the automatic categorisation of android applications , 2012, 2012 IEEE Consumer Communications and Networking Conference (CCNC).

[14]  Kensuke Fukuda,et al.  Enhancing the Performance of Mobile Traffic Identification with Communication Patterns , 2015, 2015 IEEE 39th Annual Computer Software and Applications Conference.

[15]  Jan Muntermann,et al.  Towards a Taxonomy of Mobile Applications , 2007, AMCIS.

[16]  Myung-Sup Kim,et al.  Towards smart phone traffic classification , 2012, 2012 14th Asia-Pacific Network Operations and Management Symposium (APNOMS).

[17]  Deborah Estrin,et al.  A first look at traffic on smartphones , 2010, IMC '10.

[18]  Guillaume Urvoy-Keller,et al.  Toward systematic methods comparison in traffic classification , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[19]  Enhong Chen,et al.  Mobile App Classification with Enriched Contextual Information , 2014, IEEE Transactions on Mobile Computing.

[20]  Peter Holland,et al.  Can Passive Mobile Application Traffic be Identified using Machine Learning Techniques , 2015 .

[21]  Sung-Ho Yoon,et al.  Research on traffic taxonomy for Internet traffic classification , 2011, 2011 13th Asia-Pacific Network Operations and Management Symposium.