# Application-Aware Network Traffic Management in MEC-Integrated Industrial Environments
## 4 The Case for Application-Aware Network Traffic Management  
The widespread deployment of IIoT devices has enriched industrial environments, delving into a quick shift toward smart factories. This has fostered an unprecedented volume of information, enabling disruptive use cases, such as mobile asset tracking, online remote reconfiguration, and predictive maintenance. In addition, the deployment of AGVs, in particular, and of relocatable industrial equipment, in general, has led to scenarios characterized by strong mobility. In such scenarios, dynamic and quick modifications in how traffic flows traverse the network, even at service provisioning time, cannot be considered extraordinary events. Therefore, compared with former industrial environments that traditionally crafted the same product(s) for long periods, there is now the need to manage frequent, abrupt, and sometimes even unpredictable movements of industrial equipment. Furthermore, modern industrial environments typically involve multiple industrial applications running concurrently and competing for shared resources. Such applications are fueled by the data produced on the shop floor level. The best way to deliver such data is therefore critical for guaranteeing the application requirements. This calls for application-aware network traffic management, whose objective is to manage traffic by considering application-level and application-specific requirements and characteristics. The first step toward application-aware network traffic management is prioritizing mission-critical flows over non-mission-critical ones, thus programming the network infrastructure accordingly. In this regard, mission-critical flows must be delivered promptly and reliably, whereas non-mission-critical ones may be delayed or even partially dropped when necessary to free shared resources for the former. Flow prioritization concerns the capability of setting priority levels for flows based on the information they carry. Flow steering instead concerns the capability of programming the underlying network infrastructure, thus commanding the network behavior. However, as huge traffic flows might traverse the network concurrently and abruptly migrate over time, more than flow prioritization and steering are needed for backing up application-aware network traffic management. There is also the need to be able to shape traffic flows, as they traverse the network by processing packet payloads. In fact, the raison d'etre of data aggregation and filtering is to reduce the traffic passing through the network. A typical example is the aggregation of successive messages carrying temperature values in only one, which contains the average temperature of the aggregated messages. Another example is the filtering of messages carrying vibration values within the considered safety range, in order to transmit only out-of-range conditions. In both cases, the volume of data traversing the network decreases while not affecting the quality of information used by the supported applications. In contrast to flow prioritization and steering, which can be enforced by SDN-enabled NDs, data aggregation and filtering require general-purpose computing resources, going beyond traditional networking. Such resources are provided by ENs connected via high-speed links to NDs. This minimizes the overhead of transferring data back and forth between NDs and companion ENs while, to some extent, powering NDs with general-purpose hardware. However, the on-premises resources might fall short in dealing with never-seen-before circumstances. In such cases, application-aware network traffic management might require peaks of resources beyond those available. To fill this gap, we consider MEC-integrated industrial environments, where subnet gateways at the shop floor level are equipped with cellular interfaces (e.g., 4G/LTE/5G) toward MEC-enabled cell towers.