This paper introduces a modeling approach to the design and evaluation of large wireless sensor networks against the topology of the network and the monitoring application and taking into account the performance degradation due to the power consumption. The model is built by composing Stochastic Activity Network (SAN) models of the nodes and a Markovian Agent Model (MAM) of the whole network. The SAN models are used to conduct a performance analysis of the nodes (i.e. to measure their sampling time) and evaluate their mean time to discharge. The MAM is used to compose the results of the SAN model analysis into a complex topology-aware model able to evaluate the Packet Delivery Ratio (PDR) and the power consumption of the network. The possibility to model spatially distributed interdependencies featured by the MAM makes the integrated model a concrete, scalable mean to evaluate different design choices and perform meaningful what-if analyses. The model has been validated by comparing the analysis results with real node values: specifically we present the experimental results obtained by using TelosB nodes equipped with TinyOs.
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