  The internet activity records (IARs) of a mobile cellular network posses
significant information which can be exploited to identify the network's
efficacy and the mobile users' behavior. In this work, we extract useful
information from the IAR data and identify a healthy predictability of
spatio-temporal pattern within the network traffic. The information extracted
is helpful for network operators to plan effective network configuration and
perform management and optimization of network's resources. We report
experimentation on spatiotemporal analysis of IAR data of the Telecom Italia.
Based on this, we present mobile traffic partitioning scheme. Experimental
results of the proposed model is helpful in modelling and partitioning of
network traffic patterns.
