Function traffic-aware VNF migration for service restoration in an NFV-enabled IoT system

Maintaining a service continuum is crucial for providing a reliable service in an Internet-of-Things (IoT) system based on Network Function Virtualization (NFV) due to the distribution of Virtual Network Functions (VNF). We address the optimization problem of VNF migration in an NFV-enabled IoT system (NIoT), considering the dynamics of traffic volume processed by an individual IoT function. We develop an optimization model based on integer linear programming and a function traffic-aware heuristic algorithm to solve the problem. The evaluation results show that our proposed heuristic algorithm offers an approximation solution very close to the optimal VNF migration in significantly reduced time. It outperforms a benchmark solution based on Simulated Annealing in both the service restoration cost and computation time. Furthermore, our findings provide valuable insights into an investment strategy for an IoT service provider seeking to enhance the system performance in the presence of a failure.