On the Use of LoRaWAN for Mobile Internet of Things: The Impact of Mobility

Abstract

A long-range wide-area network (LoRaWAN) targets both mobile and static Internet of Things (IoT) applications; it is suited to IoT applications, which require a large coverage area while consuming less power at a low data rate; it provides a solution for transferring data between IoT devices with a minimum cost in terms of power, at the expense of higher latency. LoRaWAN was designed for static low-power long-range networks. However, several IoT solution applications involve the use of mobility. Therefore, this study investigates the usage of LoRaWAN in the field of mobile Internet of Things applications such as bike rentals, fleet monitoring, and wildlife and animal tracking applications. Using the OMNeT++ simulator, two different well-known mobility models are used to investigate the influence of mobility on the performance of mobile LoRaWAN. The results show that intense LoRaWAN networks can operate under a high velocity and varying traffic load. It can be observed that the random waypoint model combination yields a better performance, but at the cost of higher collisions and energy consumption. As a consequence, the results suggest the reconsideration of mobile IoT solutions over LoRaWAN.

Mobility of LoRaWAN Gateways for Efficient Environmental Monitoring in Pristine Sites

“…Applying mobility to the LoRaWAN networks enhances the efficiency of monitoring systems in many domains. The authors of [ 38 ] applied various mobility models under LoRaWAN channel and investigated communication quality. According to their findings, the effect of mobility on the LoRaWAN link is nearly limited to the Doppler effect and the increased number of collisions as the number of mobile end-nodes increases.…”

LP-MAB: Improving the Energy Efficiency of LoRaWAN Using a Reinforcement-Learning-Based Adaptive Configuration Algorithm

“…A wide variety of applications require or apply mobility enabled by the IoT. Mobile applications are found in traffic monitoring, smart metering, and animal tracking [ 31 , 32 ]. Through this Scenario, we are investigating the effects of mobility on the performance of EDs, by comparing various ADR mechanisms.…”

“…Through this Scenario, we are investigating the effects of mobility on the performance of EDs, by comparing various ADR mechanisms. In this work, we assess the use of the Random Waypoint Mobility Model for simulating LoRaWAN [ 32 ]. This Scenario runs for and the number of EDs varies between 100 and 700 in both the urban and the sub-urban environment, while the EDs’ speed varies from zero to five meters per second and follows an exponential distribution.…”

“…Figure 12 shows the PDR and EC of the LP-MAB scheme for a variety of network sizes (small and large network areas) using 100 EDs, for different mobility speeds, based on the Random Waypoint Mobility Model [ 32 ]. As can be seen in Figure 12 , by increasing the network size, the overall performance of the network will be degraded, regardless of its speed, the same as indicated in Scenario 4.…”

“…As can be seen in Figure 12 , by increasing the network size, the overall performance of the network will be degraded, regardless of its speed, the same as indicated in Scenario 4. It is important to note that the configured path loss model in our work is , which is appropriate for small area networks as [ 11 ], unlike the path loss model used in [ 32 ], which is usually used in large area networks.…”