Smartphone user’s traffic characteristics and modelling

Abstract

The proliferation of smartphones and the demand for all-day connectivity has brought exponential growth of global mobile data traffic. To survive the explosive progression and best serve their customers, mobile network operators need to have a better understanding of the nature of traffic carried by cellular networks. Understanding the characteristics of this traffic is important for network design, traffic modelling, resource planning, and network control. In this work we investigate the basic characteristics of smartphone traffic, identifying and understanding the impact of context (location, time, physical interface) on smartphone usage for calls, messages and data traffic. In order to identify and characterize patterns in the user traffic generated by smartphone devices in the mobile networks, we employ naturalistic logging methodology based on non-obtrusive background data collection while aiming for a highly diverse study participant’s backdrop. Our statistical results present a comprehensive analysis on user habits while using their smartphones on a daily or weekly basis. By taking advantage of the gathered user logs and the statistical analysis of the traffic characteristics, we attempt to design a mobile traffic generator that will create synthetic voice, message and data traffic according to the observed real life traffic characteristics. The generated mobile traffic scenarios can be used not only for modelling the mobile operators’ network (such as 3G and 4G), but also WiFi, mobile ad hoc and sensor networks.