A Robust Regression Model for Handover Prediction In Wireless Networks


Shakhawan H. Wady1, Kamalrulnizam A. Bakar2 & Kayhan Z. Ghafoor3

1 Mathematics Department, School of Science Education, University of Sulaimani, Sulaimani, Iraq.
2 Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Malaysia.
3 Faculty of Engineering, School of Computing, Koya University, Koya, Iraq.




Abstract
The recent applications of wireless networks demand high Quality of Service (QoS) and
mobility management between access networks. For this reason, emergent Advances in
IEEE 802.11 standards have been witnessed to achieve seamless communication
between mobile nodes. However, since existing handover mechanisms have
shortcomings in terms of mobility handover cost and latency, more robust handover
decision approach should be considered. To this end, in this research, we propose a
decision approach to accurately trigger handover process between current and next
access point. The proposed approach incorporates robust regression model is to predict
the received signal strength (RSS) of the wireless channel between the mobile node
(MN) and the access point. Thus, the MN makes an accurate handover decision as well
as layer 3 handover process occurs in advance to the one in layer 2. Our theoretical
analysis and simulation results show that the proposed handover decision approach is far
superior to the existing handover decision schemes in terms of handover latency and
cost.
 



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