%0 Journal Article %1 noauthororeditor %A K.Gunasekaran, %D 2012 %J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) %K Clustering Partitioning Statistical Traffic User measurement methods session techniques threshold %N 6 %P 41-49 %R 10.5121/ijcseit.2012.2604 %T IDENTIFICATION AND INVESTIGATION OF THE USER SESSION FOR LAN CONNECTIVITY VIA ENHANCED PARTITION APPROACH OF CLUSTERING TECHNIQUES %U http://airccse.org/journal/ijcseit/papers/2612ijcseit04.pdf %V 2 %X This paper mainly presents some technical discussions on the identification and analyze of “LAN usersessions”. The identification of a user-session is non trivial. Classical methods approaches rely on threshold based mechanisms. Threshold based techniques are very sensitive to the value chosen for the threshold, which may be difficult to set correctly. Clustering techniques are used to define a novel methodology to identify LAN user-sessions without requiring an a priori definition of threshold values. We have defined a clustering based approach in detail, and also we discussed positive and negative of this approach, and we apply it to real traffic traces. The proposed methodology is applied to artificially generated traces to evaluate its benefits against traditional threshold based approaches. We also analyzed the characteristics of user-sessions extracted by the clustering methodology from real traces and study their statistical properties.

@article{noauthororeditor, abstract = {This paper mainly presents some technical discussions on the identification and analyze of “LAN usersessions”. The identification of a user-session is non trivial. Classical methods approaches rely on threshold based mechanisms. Threshold based techniques are very sensitive to the value chosen for the threshold, which may be difficult to set correctly. Clustering techniques are used to define a novel methodology to identify LAN user-sessions without requiring an a priori definition of threshold values. We have defined a clustering based approach in detail, and also we discussed positive and negative of this approach, and we apply it to real traffic traces. The proposed methodology is applied to artificially generated traces to evaluate its benefits against traditional threshold based approaches. We also analyzed the characteristics of user-sessions extracted by the clustering methodology from real traces and study their statistical properties. }, added-at = {2018-04-09T08:43:10.000+0200}, author = {K.Gunasekaran}, biburl = {https://www.bibsonomy.org/bibtex/2c6ece0c07e9f21e923cf192119faeccc/ijcseit}, doi = {10.5121/ijcseit.2012.2604}, interhash = {bea99cea83e36b440d6e9e29ea744475}, intrahash = {c6ece0c07e9f21e923cf192119faeccc}, issn = {2231-3117 [Online] ; 2231-3605 [Print]}, journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)}, keywords = {Clustering Partitioning Statistical Traffic User measurement methods session techniques threshold}, language = {English}, month = dec, number = 6, pages = {41-49}, timestamp = {2018-04-09T08:43:10.000+0200}, title = {IDENTIFICATION AND INVESTIGATION OF THE USER SESSION FOR LAN CONNECTIVITY VIA ENHANCED PARTITION APPROACH OF CLUSTERING TECHNIQUES}, url = {http://airccse.org/journal/ijcseit/papers/2612ijcseit04.pdf}, volume = 2, year = 2012 }