SDNQ: A Novel SDN Controller for the Management of IoT Video Flows in the Edge/Cloud Continuum
Pouria Pourrashidi Shahrbabaki, Rodolfo W. L. Coutinho, Yousef R. Shayan · 2024
Internet of Things (IoT) has been used to empower smart environments and applications in different domains. In some IoT systems, IoT cameras live stream video frames to edge or cloud servers to be processed by machine learning (ML) models. The processing of the video frames will aim to detect and recognize objects or other entities of interest. However, the processing of IoT video frames at cloud servers often relies on high latency due to network congestion and high load at the cloud servers. In this paper, we proposed the SDNQ controller, a software-defined networking (SDN) controller that uses a reinforcement learning (RL) agent to decide how to route and where to process video frames from IoT flows. The proposed solution considers the network and servers' status, the latency experienced by admitted video flows, and the video flows' latency requirements when deciding the routing path and the destination edge or cloud server to process a newly admitted IoT video flow. Numerical results show that the proposed solution outperforms related works at the cost of blocking a low fraction of IoT flows.