| Abstract |
With the advent of increasingly large smart-city and IoT deployments, meeting communication requirements in terms of throughput and delay becomes more and more challenging. Network performance analyses must be carefully addressed, usually through simulation software. Because of the large-scale nature of the IoT, traditional simulation methods do not scale well. Thus, in this article, we present two original contributions that provide scalability to network performance simulations. First, we introduce the concept of multi-layered analysis for large-scale networks and, second, we provide a method to quickly associate propagation measures to user equipment. The proposed concept is based on the de-coupling of the access and the user layer and the introduction of a so-called grid layer created by pre-computing propagation measures in the considered area. These propagation data are then ready to be used in the network performance simulation. To show the efficacy of the proposed approach, several realistic use cases are analyzed along with a comparison of the time needed to simulate with and without our grid-based methodology. Numerical results show that a significant reduction of computational time is achieved by employing our approach, especially in large-scale networks. Experiments were also performed to study the trade-off between grid granularity, RSS precision errors and computational time, showing that the method can be flexibly adapted to the planners' requests. © 2018 IEEE. |
