Profitable Energy-Efficient UPF and Application Placement and Routing in Dynamic 5G Edge

The development of 5G networks has enabled diverse applications with stringent communication and computation requirements. Ensuring timely operation for these applications requires proximity to compute and network resources, such as edge servers and User Plane Functions. With control over network resources and partial ownership of compute resources, Mobile Network Operators (MNOs) can assume a larger role in service orchestration within a multi-owner edge infrastructure. However, the increasing demand for edge applications often exceeds MNO capacity. To address this, some user requests can be offloaded to third-party cloud operators, expanding capacity but incurring costs and reducing profitability. Beyond profit, energy consumption is a key concern, particularly as we transition toward 6G. Addressing high energy consumption adds complexity to resource orchestration, as it directly conflicts with the goal of maximizing profit. Moreover, in dynamic edge environments, frequent service migrations increase orchestration overhead and can negatively impact user experience. Navigating these trade-offs requires an effective optimization approach. To this end, we formulate a multi-objective optimization problem for demand placement and routing, aiming to maximize MNO profit while minimizing energy consumption and migration overhead. Given its NP-hard nature, we propose a ranked greedy heuristic to effectively balance these objectives. Simulation results show that our approach outperforms benchmark algorithms in both static and dynamic scenarios, achieving near-optimal performance and deviating less than 7% from the optimal solution.