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Joseph Stephen Bassi
University of Maiduguri
Computer Science & IT Electrical & Electronics Engineering

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Impact of Packet Inter-arrival Time Features for Online Peer-to-Peer (P2P) Classification Bushra Mohammed Ali Abdalla; Mosab Hamdan; Mohammed Sultan Mohammed; Joseph Stephen Bassi; Ismahani Ismail; Muhammad Nadzir Marsono
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (910.388 KB) | DOI: 10.11591/ijece.v8i4.pp2521-2530

Abstract

Identification of bandwidth-heavy Internet traffic is important for network administrators to throttle high-bandwidth application traffic. Flow features based classification have been previously proposed as promising method to identify Internet traffic based on packet statistical features. The selection of statistical features plays an important role for accurate and timely classification. In this work, we investigate the impact of packet inter-arrival time feature for online P2P classification in terms of accuracy, Kappa statistic and time. Simulations were conducted using available traces from University of Brescia, University of Aalborg and University of Cambridge. Experimental results show that the inclusion of inter-arrival time (IAT) as an online feature increases simulation time and decreases classification accuracy and Kappa statistic.
Co-Authors Bushra Mohammed Ali Abdalla Ismahani Ismail Mohammed Sultan Mohammed Mosab Hamdan Muhammad Nadzir Marsono