RT Journal Article
T1 Mobility management: deployment and adaptability aspects through mobile data traffic analysis
A1 Sánchez Segura, María Isabel
A1 Zeydan, Engin
A1 Oliva Delgado, Antonio de la
A1 Tan, A. Serdar
A1 Yabas, Utku
A1 Bernardos Cano, Carlos Jesús
AB The expected boost in mobile data traffic and the evolution towards the next generation of networks are making cellular operators reconsider whether current approaches for handling mobility could be improved, according to the characteristics of the mobile traffic that actually flows through real networks. In this work, we make use of extensive analysis of real network traces to infer the main characteristics of mobile data traffic for a particular operator. Our analysis focuses on the features related to mobility, i.e., location information, number of handovers, or duration of the data traffic exchange. New techniques to gather the mobility characteristics of the user based on data and control packets correlation are designed and applied to compare the gains of deploying different mobility management approaches.
PB Elsevier B.V.
SN 0140-3664
SN 1873-703X (online)
YR 2016
FD 2016-12-01
LK https://hdl.handle.net/10016/25980
UL https://hdl.handle.net/10016/25980
LA eng
NO The research leading to these results has received funding from the EU Seventh Framework Programme (FP7/2007-2013) under grant agreement 318115 (Connectivity management for eneRgy Op- timised Wireless Dense networks, CROWD). The work of Antonio de la Oliva has also been funded by the EU H2020 5G-Crosshaul Project (grant no. 671598).
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