Estimating performance in dense IEEE 802.11 networks with E-AFTER

Performance estimation can be used to improve IEEE 802.11 networks. Not only can it be used when designing the network to find a suitable number of APs to cover an area, but it can also be applied to several performance-maintaining tasks, such as load-balancing and interference control. MAPE is a framework that can provide good throughput estimations in multi-hop IEEE 802.11 networks. However, dense, interference-prone scenarios have an inherently higher complexity due to the number of interactions between the transmitting nodes. Since the original proposal of MAPE does not consider the interference between concurrent transmissions, its accuracy tends to decrease in such scenarios. This work focuses on enhancing MAPE by proposing several changes that model extra network interactions to improve its accuracy in dense IEEE 802.11 networks while maintaining short execution times. The evaluation of this enhanced version, called E-AFTER, shows a 158% increase in correlation between the estimates and the actual network performance and the reduction of estimation error in comparison to the original MAPE.