Load-Aware Multi-Objective Optimization of Controller and Datastore Placement in Distributed Sdns

In distributed Software Defined Networking (SDN), multiple controllers need to maintain a consistent view of the network state among themselves using consensus algorithms, introducing additional communication overhead and network delay, especially in large-scale networks. Therefore, optimizing controller placement presents significant challenges, as it must account not only for the delay between switches and controllers but also for the delay introduced by consensus algorithms. Additionally, SDN controllers have limited capacity in terms of the number of switches they can manage and the network events they can process. Improper placement of controllers can lead to longer message processing times, increased queuing delays, or even controller failures. Thus, achieving balanced workloads among controllers is essential. This study introduces and validates a practical Flow Setup Time (FST) model to measure controller response times. We proposed an advanced multi-objective optimization approach that incorporates the Variance of Load Balancing (VOLB), to determine the optimal placements of controllers and datastore nodes involved in processing consensus algorithms. Furthermore, we applied this optimization method to different types of real networks from the Internet Topology Zoo dataset. Based on experimental findings, we identified key factors to consider when selecting optimal placement strategies, including the trade-offs between the number of controllers, the number of datastore nodes, FST, and VOLB.