Proactive mobility management of software defined wireless networks

Wireless networks are a very complex and dynamic environment that requires proper management to optimise its performance. With a tremendous increase in the number of user devices and their data traffic, wireless networks are becoming denser. Therefore, optimising mobility management becomes a crucial challenge. In heterogeneous wireless networks, the usage of multiple wireless interfaces is inefficient and suboptimal. Solutions require modifications to the user device limiting the use cases. Reactive approaches are too slow to react and solutions often reside on the user side, which creates suboptimal perdevice optimisations. To tackle these challenges we use SDN. SDN monitors the network by collecting multiple metrics on the network side and creates a global overview of the network. This overview can be used in SON algorithms to proactively trigger global optimisations. We create and use different SDN frameworks for different wireless technologies and create SON algorithms on top to optimise mobility. In heterogeneous wireless networks, we introduce ORCHESTRA, an SDN framework to manage different devices and do packetlevel dynamic and intelligent handovers, load balancing and replication. On top of ORCHESTRA we present a novel MIQP load-balancing optimization problem formulation for mobility management which can double the network-wide throughput across different scenarios. To avoid user device modifications, we introduce the HuMOR framework for handover management in WiFi. On top of HuMOR we introduce ABRAHAM a handover algorithm that uses multiple metrics to predict the future state of the network and optimize the AP load. We show that ABRAHAM can achieve a 139% throughput improvement over the IEEE 802.11 handover algorithm. To demonstrate that our WiFi solution is capable to address different wireless contexts, we use the same principles in mobile networks. On top of an OpenRAN compliant framework dRAX, we introduce MOLA_ADNA. This adaptive and QoS aware handover algorithm takes multiple metrics into account to do network level optimization of the cell load. We show that the mean throughput with MOLA-ADNA was higher by 25% compared to A3. Finally, proper network element configuration is also crucial for network performance and mobility management. We, therefore, create the ALPACA algorithm on top of dRAX to optimise the PCI value of cells in mobile networks. ALPACA adapts to dynamic network topology changes and continuously optimizes the network. The results show that ALPACA can resolve all collisions and confusion for up to 1000 cells and minimize the effects of inevitable modulo PCI issues.

Publication year:2022

Keywords:Doctoral thesis

Accessibility:Open