Wireless Sensor Networks (WSNs) are often used for environment monitoring, an application which requires reliable routing of messages from source to sink nodes via multi-hop networks. Prior to installing such WSNs, engineers commonly analyse the network using discrete event simulation (DES). Whilst sophisticated simulators such as Castalia and TOSSIM take into account many low-level features of WSNs, their biggest drawback is the lack of scalability. This inhibits design-time system optimisation for large or complex networks. In this paper, we discuss how Population CTMC (PCTMC) models, used in conjunction with mean-field analysis, can possibly mitigate this problem. To illustrate the potential of PCTMC models in the WSN domain, we present a PCTMC model for a failsafe, dynamic routing protocol, which we implemented in Castalia. We show that the mean-field solution for the model yields good qualitative agreement with corresponding low-level simulations, but at a fraction of the computational cost. In particular we see good agreement for average metrics describing buffer occupancy and data flow behaviour. Moreover, our PCTMC model even produces good results when packets are lost due to channel interference.
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