Title
Learning Based Proactive Handovers in Heterogeneous Networks.
Abstract
Today, the number of versatile real-time mobile applications is vast, each requiring different data rate, Quality of Service (QoS) and connection availability requirements. There have been strong demands for pervasive communication with advances in wireless technologies. Real-time applications experience significant performance bottlenecks in heterogeneous networks. A critical time for a real-time application is when a vertical handover is done between different radio access technologies. It requires a lot of signalling causing unwanted interruptions to real-time applications. This work presents a utilization of learning algorithms to give time for applications to prepare itself for vertical handovers in the heterogeneous network environment. A testbed has been implemented, which collects PHY (Physical layer), application level QoS and users context information from a terminal and combines these Key Performance Indicators (KPI) with network planning information in order to anticipate vertical handovers by taking into account the preparation time required by a specific real-time application.
Year
DOI
Venue
2013
10.1007/978-3-319-04277-0_5
Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Keywords
DocType
Volume
Vertical Handover,Heterogeneous Network,Key Performance,Indicator,Machine Learning,Quality of Experience
Conference
125
ISSN
Citations 
PageRank 
1867-8211
0
0.34
References 
Authors
4
5