Fast Decision Algorithms for Efficient Access Point Assignment in SDN-Controlled Wireless Access Networks

Global optimization of access point (AP) assignment to user terminals requires efficient monitoring of user behavior, fast decision algorithms, efficient control signaling, and fast AP reassignment mechanisms. In this scenario, software defined networking (SDN) technology may be suitable for network...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management 2019-09, Vol.16 (3), p.1059-1070
Main Authors: Fondo-Ferreiro, Pablo, Mhiri, Saber, Lopez-Bravo, Cristina, Gonzalez-Castano, Francisco J., Gil-Castineira, Felipe
Format: Article
Language:English
Subjects:
5G mobile communication
5G mobile communications
Access control
admission control
Algorithms
Allocations
Decisions
Global optimization
Handover
History
Millimeter waves
Monitoring
Network management systems
Network topologies
optimization
Prediction algorithms
Quality of service
Signal monitoring
Signaling
Software-defined networking
Switches
Switching theory
Terminals
User behavior
Wireless networks
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Summary:Global optimization of access point (AP) assignment to user terminals requires efficient monitoring of user behavior, fast decision algorithms, efficient control signaling, and fast AP reassignment mechanisms. In this scenario, software defined networking (SDN) technology may be suitable for network monitoring, signaling, and control. We recently proposed embedding virtual switches in user terminals for direct management by an SDN controller, further contributing to SDN-oriented access network optimization. However, since users may restrict terminal-side traffic monitoring for privacy reasons (a common assumption by previous authors), we infer user traffic classes at the APs. On the other hand, since handovers will be more frequent in dense small-cell networks (e.g., mmWave-based 5G deployments will require dense network topologies with inter-site distances of ~150-200 m), the delay to take assignment decisions should be minimal. To this end, we propose taking fast decisions based exclusively on extremely simple network-side application flow-type predictions based on past user behavior. Using real data we show that a centralized allocation algorithm based on those predictions achieves network utilization levels that approximate those of optimal allocations. We also test a distributed version of this algorithm. Finally, we quantify the elapsed time since a user traffic event takes place until its terminal is assigned an AP, when needed.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2019.2925506