RT Conference Proceedings
T1 Handover Prediction Integrated with Service Migration in 5G Systems
A1 Abdah, Hadeel
A1 Barraca, João Paulo
A1 Aguiar, Rui L.
AB As the research community inclines toward adopting increasingly complex techniques for future networks, and simple methods are often ignored, being labeled as trivial. In this paper, we argue that simple methods can sometimes outperform more sophisticated ones. We demonstrate that by evaluating two prediction mechanisms to forecast mobile user’s handovers exploiting user-network association patterns. We perform a series of experiments on real-world data, evaluating the performance characteristics of such methods over more sophisticated and complex prediction techniques. Furthermore, we discuss how to easily bootstrap these mechanisms into the 5G network architecture. We suggest the use of these methods associated with Multi-access Edge Computing (MEC) scenarios, as a mean to identify favorable edge nodes to host the mobile applications, to best provide continuous and QoS-aware service for mobile users.
PB IEEE
SN 978-1-7281-5089-5
YR 2020
FD 2020-07-27
LK https://hdl.handle.net/10016/31343
UL https://hdl.handle.net/10016/31343
LA eng
NO This paper has been presented at ICC 2020 - 2020 IEEE International Conference on Communications (ICC)
NO This work is funded by FCT/MEC through national funds and when applicable co-funded by FEDER - PT2020 partnership agreement under the project UID/EEA/50008/2019, Fundacao para a Ciencia e Tecnologia under grant SFRH/BD/136361/2018, and by the European Commission through the H2020 project 5GROWTH (Project ID 856709).
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RD 1 sept. 2024