Performance Analysis of IoT networks with Mobile Data Collectors

Efficient data collection has been treated as a key challenge especially in the sparsely deployed Internet of Things (IoT) networks. Compared with the conventional data collection methods using static sinks, mobile data collectors (MDCs) are considered as a more efficient approach where MDCs transfer data from sensors to access points (APs) by roaming over different geographical regions. In this work, we propose an analytical framework to study the coverage performance of IoT with MDCs where MDCs follow a simple random waypoint (SRWP) mobility model. To characterize the interference distribution of the whole network, we first derive exact expressions for the average contact time (CT) and inter-contact time (ICT) between a typical sensor and its associated MDC. Then we determine the active probability of the typical sensor by using the derived CT and ICT. The coverage probability is finally derived by taking into account the communication range of sensors, velocity of MDCs, density of sensors and MDCs, and the SINR threshold. Our results reveal the fact that the velocity of MDCs has little effect on coverage probability while a higher velocity can significantly lower the end-to-end delay.