A Scalable Hierarchically Distributed Architecture for Next-Generation Applications

The rigidity of traditional network architectures, with tightly coupled control and data planes, impairs their ability to adapt to highly dynamic requirements of future application domains. While Software-Defined Networking (SDN) can provide the required dynamism, it suffers from scalability issues. Therefore, efforts have been made to propose alternative decentralized solutions, such as the flat distributed SDN architecture. Such alternatives address the scalability problem for mainly local flows, but are impaired by a substantial increase in the overhead for cross-domain flow setup. To manage the trade-off between scalability and overhead, there is a need for intermediate hierarchical solutions. However, these have not been explored to the complete potential so far. Furthermore, the Network Function Virtualization (NFV) paradigm complements SDN by offering computational and storage services in the form of Virtual Network Functions (VNFs). When integrated seamlessly, both SDN and NFV can offer solutions to the problems posed by highly dynamic application domains. Hence, this work proposes a scalable hierarchical SDN control plane architecture for SDN/NFV-based next-generation application domains such as immersive media delivery system. We have implemented the proposed architecture based on the well-known state-of-the-art ZeroSDN controller. To evaluate the performance of the architecture, we have implemented an on-demand immersive media (point cloud) streaming application and varied the load on the control plane using the background traffic. To benchmark our solution, we have evaluated its performance in comparison with the centralized and flat distributed architectures. We show that the proposed architecture performs better than the rest in terms of scalability, lost flows, and processing latency. Our study shows that the proposed architecture when distributed to three controllers, accepts 23% more flows with almost 70% reduced processing latency compared to the state-of-the-art ONOS controller.