Multi-channel wireless traffic sensing and characterization for cognitive networking

Authors:
Bheemarjuna Reddy Tamma;Nicola Baldo;B. S. Manoj;Ramesh R. Rao
Affiliations:
California Institute for Telecommunications and Information Technology, UC San Diego;Centre Tecnològic de Telecomunicacions de Catalunya, Barcelona, Spain;California Institute for Telecommunications and Information Technology, UC San Diego;California Institute for Telecommunications and Information Technology, UC San Diego
Venue:
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Year:
2009

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Abstract

Traffic sensing and characterization is an important building block of cognitive networking systems; however, it is very challenging in multi-channel multi-radio wireless networks. The contributions of this paper include the following: (i) a discussion of packet sampling for traffic sensing in multi-channel wireless networks, (ii) a comparison of various time-based sampling strategies using the Kullback-Leibler Divergence (KLD) measure, (iii) a study of the effect of the sampling parameters on the accuracy of the sampling strategies, (iv) the proposal of a new metric (Traffic Intensity) which estimates the busyness of channels by taking into consideration not only the successfully received packets but also corrupt or broken packets, and (v) some preliminary results on the characterization of a campus 802.11 network environment in a spatio-temporal fashion.