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The connectivity in IIoT systems could exploit well-established communication protocols to reduce network configurations and customizations. However, the increasing integration of communication into automation aspects makes IIoT systems more complex and prone to errors (e.g., device failures, mistakes in configuration). Given that failure in communication may be catastrophic in industrial applications using IIoT, it is essential to use proper system models and verification schemes to increase the level of certainty in IIoT systems. There are different approaches to create system models, such as theoretical inference and simulation tests.

An important reference in IIoT wireless system design is modeling data traffic patterns to capture and predict the dynamic behavior of systems and handle system complexity. However, we initially need to understand the theoretical basis of inference models and the conditions underlying their effectiveness before choosing the method apt to IIoT environments and service characteristics. This justifies a rising need for network simulation platforms and testbeds that emulate real-world industrial systems and perform system-level verification [170]. The simulation frameworks could also assist in performance evaluation of wireless networks for the next-generation factories and process automation systems [171].