Stochastic modeling of depth based routing in underwater sensor networks

Interest in underwater wireless sensor networks (UWSNs) based on acoustic communication has rapidly grown over the last decade. In this field, the design of energy-efficient communication protocols is a crucial task as battery replacement may be unfeasible in practical scenarios. While routing protocols play a pivotal role in determining the efficiency of UWSNs, only a few studies investigate analytical stochastic models for their quantitative analysis and optimization. In this work, we consider a popular routing protocol for UWSNs, namely Depth Based Routing (DBR), and introduce a stochastic model for numerically deriving important performance indices, like the end-to-end delay, the energy consumption and the delivery probability, in terms of the configuration parameters. The model accounts for peculiar factors of UWSNs, including the impact of node deployment and mobility, and the high transmission loss of the acoustic channel. We present insights that are useful in setting DBR configuration parameters to optimize the trade-off between delivery probability, energy consumption and end-to-end delay.