# From Brown-Field to Future Industrial Networks, a Case Study
## 5 Discussion and Future Directions  
IT-OT converged networks ought to accommodate traffics with different characteristics and requirements. There are ambiguities on the specific obligatory performance metrics, other than the general network performance criteria, i.e., delay throughput and packet drop rate, as well as lack of recommendations for configuration. It cannot be a fair assumption to classify IT traffic patterns in future networks as burst flows, that is considering the current trend in industry and academia for further digitalization of the factories and migration of some of the control systems functionalities to the fog or the cloud, namely Virtual Programmable Logic Controllers (VPLCs). Hence, some of the IT traffic might project expected periodic communication patterns of OT traffic. The gap in the literature is even more palpable for the transformation of brown-fields, where there is not enough insight from the existing networks, nor any recommended approach for moving forward. Lack of available data from brown-field also leaves the researchers with  
Figure 7: Production cyclic work-flow projected from network traffic. simulated and emulated data for traffic profiling and flow modeling, where the models do not perform well when applied to real traffic data. As it was shown, the assumption of singular traffic class communication pattern on the logical division of OT traffic does not hold for brown-field traffic. Characterization of the network traffic is the first step for configuration and performance management of the network. The existing methods for characterization and profiling the traffic fall short of meeting the scalability requirements of IT-OT converged traffic. A sophisticated network management system requires an accurate and thorough analysis of the network components about the resources and criteria for performance management, among other important parameters. Affected by the previously discussed increased complexity, the accurate analysis of the network performance with flow-level measurement will potentially be even more difficult. Performance dynamic mixture characterization can potentially reduce the complexity of network management for the integration of new traffic flows. The integration of new technologies and consequently adding traffic to the network needs to be carried out without, or with a minimum, interruption of the ongoing regular workflows. A sensible approach would be a configuration that minimizes the possibility of traffic congestion which has a direct negative effect on network performance in terms of delay and packet drop rate. Following the discussion in Figure 7, the peaks of the patterns happen when a larger amount of data is transmitting in the network, e.g., larger packets, a higher number of transmissions or a combination of both. Hence, integrating any new IT-OT traffic or flow will increase the risk of congestion, even if the flow configuration of the intended communication does not show any restrictions caused by simultaneous flow transmissions in source or destination. On the contrary, a flow can be configured and added to the network as long as throughput dynamics show the availability of resources. The same approach can be applied as a batch replacement, or integration, to ensure the network's uninterrupted operation by estimating the available resources in time interval where the anticipated resource is proportionally lower than the dynamic peaks. Modeling of IT-OT networks for monitoring and anomaly detection purposes is one of the future challenges since the huge number of flows in converged network traffic will introduce the curse of dimension, and its high computational costs, to network monitoring and performance management. The proposed method set the monitoring scope on the performance of the network, with a level of abstraction that reveals regular workflows.