success probability because it cannot compensate the impact of interference. On the other hand, one sees that increase in the number of replicas per packet could be leveraged to increase reliability of communications. However, there is a saturation point in scenarios with higher densities of nodes, where increasing number of replicas increases traffic load significantly, and may even reduce reliability of communications. Example of such event was observed in Fig. \[oo1\] for $n_1\ge5$. Finally, the rate of increase in reliability of communications by increasing the number of APs, which reduces the communications’ distance, and increasing the bandwidth, which decreases the collision probability, could be observed in Fig. \[scc\].

![Scalability analysis versus required reliability ($K=1$, $\lambda_1$=3.2). []{data-label="scc"}](Figs/Sim/scal_vs_cov.eps){width="3.5in"}

Conclusion
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A tractable analytical model of reliability in large-scale heterogeneous IoT networks has been presented as a function of IoT traffic intensity and access network’s resources. This model has been employed to analyze the impacts of resource provisioning at the network-side and operation control at the device-side on reliability and battery lifetime of IoT devices. The derived expressions illustrate the rate of increase in reliability and battery lifetime achieved by increasing the bandwidth of communications and number of APs. Our analyses indicated that 