# On the Use of LoRaWAN for Mobile Internet of Things: The Impact of Mobility
## 2 Related Work  
The work in [4] evaluated the performance of an unmanned aerial vehicle (UAV) integrated with LoRa technology. The case study focused on finding the impact of the number of UAVs and their flying speed on the overall performance of the UAV-LoRa integrated system using simulation tools. The study included eight different UAV mobility models (random direction, random walk, Gauss-Markov, random waypoint, semi-random circular movement, reference point group mobility, smooth turn, and pathway mobility). It concluded that the best results can be achieved with the random direction mobility model, where lower delays and jitter were achieved with a better delivery rate. However, the focus of this study was on the UAV networks. The performance of real-world mobile LoRaWAN applications was evaluated in [12]. The authors targeted the evaluation of the latency that traffic may experience while moving from mobile end devices to LoRaWAN network servers. Their experiments consisted of a few mobile devices with a preconfigured itinerary, which was chosen to keep the mobile devices under the coverage of gateways. Mobile end devices were moving in a car with an average speed of 17 km/h. The results of the experimental evaluation indicate that mobile end devices' traffic experiences the same delay as that of static devices. This is expected, as mobile devices' paths are preconfigured to stay within the coverage area of LoRaWAN gateways, and no interruption of communication was anticipated. The work in [13] proposed a wildlife monitoring system that incorporated LoRaWAN and an opportunistic mobile network (OMN). End nodes were assumed to be fitted with LoRa and Bluetooth Low Energy (BLE) technologies, where LoRa can be used for long-range communication and BLE can be used for P2P communication among the end nodes. The proposed system was evaluated using a network simulator. Regarding end device mobility, the proposed work used the random waypoint mobility model to express device mobility, as well as another mobility model that was derived from ZebraNet GPS data. The latter was imported to model real animal mobility behaviors and movement. Nodes were simulated with a mobility speed ranging between 10 and 30 km/h for the random waypoint mobility model. The authors of [14] also considered mobility in their proposed work. However, their paper mainly focused on enhancing the adaptive data rate (ADR) mechanism for LoRaWAN based on estimating the next positions of mobile end devices. This information, then, can be optimized by a LoRaWAN network server to determine the best configuration parameters for an end device. The authors proposed a formula to calculate the estimated positions based on different criteria. Testbeds were used to evaluate the proposal with three gateways and five end devices. The results show an improvement in the overall performance of the system when using the enhanced ADR. Thus, the work overall reflects the importance of the impact of mobility on the performance of LoRaWAN. The authors of [15] also considered the impact of mobility on the ADR mechanism. They claimed that the mobile devices' locations may change by the time that a new ADR configuration parameter arrives at the end devices from the network server. Consequently, the new parameters would no longer be suitable, due to the movement of the devices to new locations. Their proposal was evaluated using the NS-3 simulator for different scenarios consisting of one gateway. The work assumed that only 50% of simulated end devices were mobile and the rest are static. The random walk model was used to model end devices' mobility, with a minimum speed of 0.5 m/s and a maximum speed of 1.5 m/s. The benefits of ADR were also investigated for mobile LoRaWAN scenarios in [16]. Their experiments involved mounting LoRa end devices on postal tracks that drive on fixed routes around the city of Antwerp, Belgium. The experiments consisted of 15 end devices and a few gateways.