Virtualized Radio Access Network (vRAN) architectures and Multiple-access Edge Computing (MEC) systems constitute two key solutions for the emerging Tactile Internet applications and the increasing mobile data traffic. Their efficient deployment however requires a careful design tailored to the available network resources and user demand. In this paper, we propose a novel modeling approach and a rigorous analytical framework, MvRAN, that minimizes vRAN costs and maximizes MEC performance. Our framework selects jointly the base station function splits, the fronthaul routing paths, and the placement of MEC functions. We follow a data-driven evaluation method, using topologies of 3 operational networks and experiments with a typical face-recognition MEC service. Our results reveal that MvRAN achieves significant cost savings (up to 2.5 times) compared to non-optimized C-RAN or D-RAN systems, and that MEC pushes the vRAN functions to RUs and hence can increase substantially the network cost.
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