Robust SFC Placement in Next Generation Multi-Domain IoT Networks Under Resource Demand Uncertainty

Network Function Virtualization (NFV) facilitates on-demand and flexible service provisioning to meet the escalating demands of Internet of Things (IoT) applications, enabled by Service Function Chain (SFC) technique. The widespread deployment of 5G has connected a massive number of devices and users to IoT networks, accelerating the expansion of IoT scales. IoT users’ service requirements exhibit heightened diversity and dynamism. Consequently, the SFC placement problem in Next Generation Multi-domain IoT (NGMIoT) networks has garnered significant attention. How to efficiently place SFCs under uncertain resource demands to adapt to evolving service request dynamics poses substantial challenges. Therefore, this paper investigates the Robust SFC Placement (RSFCP) problem in NGMIoT networks under resource demand uncertainty. Specifically, we formulate the RSFCP problem as an integer linear programming model to minimize overall SFC placement cost while ensuring service quality. We further prove the RSFCP problem is NP-hard and propose a greedy strategy based heuristic SFC placement algorithm to solve it. Finally, extensive simulation experiments are conducted to evaluate performance, demonstrating that the proposed algorithm outperforms benchmark mechanisms in terms of service acceptance rate and placement cost.