Assessing Genetic Algorithms for Placing Flow Processing-aware Control Applications

Future wireless access networks, such as 5G networks, demand very high traffic and a broad variety of network functions. While the former needs efficient management of the underlying backhaul network, the latter ensues a large amount of data processing. Finding good locations for data processing is a non-trivial task as data processing imposes many requirements on network resources but is crucial for network performance. In previous work, we have introduced the concept of control applications that perform both network control and data flow processing, tackling both aforementioned challenges simultaneously. To model this, we have formulated the Flow processingaware Control Application Placement Problem (FCAPP) and described first placement solution approaches. In this work, we assess whether Genetic Algorithms (GAs) are a viable approach for solving FCAPP.