Exploiting adaptive window techniques to reduce TCP congestion in mobile peer networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
A unified QoS-inspired load optimization framework for multiple access points based wireless LANs
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
ICWMC '10 Proceedings of the 2010 6th International Conference on Wireless and Mobile Communications
A first look at cellular machine-to-machine traffic: large scale measurement and characterization
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Traffic sources measurement and analysis in UMTS
Proceedings of the 1st ACM workshop on High performance mobile opportunistic systems
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Traffic shaping effect may have significant impact on end-to-end Quality of Service (QoS) provisioning. Therefore, it should be carefully studied in order to allow the creation of appropriate traffic models to be used for simulations. First, to demonstrate the traffic shaping effect, we present statistical analyses on real-time measurements of diverse traffic sources (voice and video over IP) in a 3G network. By comparing the statistical distributions of the packet inter-arrival times for both the forward and backward direction, we can demonstrate directly the end-to-end traffic shaping effect introduced by the IP core network. Hence, we argue that distributed QoS management approach is needed. Additionally, we give the mean, variance, mean standard deviation, skewness, and kurtosis of the inter-arrival times, which can be used as input for simulation models. The accurate validation of the probability distributions is ensured by the Wolfram Mathematica and Crystal Ball statistical tools. Second, for the same set of measurements, we propose and defend with evaluations the use of the gamma distribution as best fitting function to traffic dynamics. Our proposal is applicable for traffic environments found in delay-tolerant networks, opportunistic networks, Internet of Things, sensor networks etc.