KATAJA/New prod. Develop./Asik

Future fifth-generation (5G) networks will provide ultra high-bandwidth, low-latency, and reliable Internet connectivity to meet the quality-of-service (QoS) requirements of diverse applications (e.g., autonomous driving or critical IoT applications). Fog radio access networks (Fog-RAN) is a promising networking architecture to achieve the desired QoS in a cost-efficient manner. Besides, network slicing (NS) enables mobile network operators (MNOs) to efficiently lease a physical network to multiple tenants (e.g., vertical industries), thus increasing their revenues. However, existing NS solutions cannot proactively upscale or downscale the slices based on tenants' future traffic and resource demands. This project proposes to design data-driven intelligent Fog-RAN slicing mechanisms to efficiently allocate the RAN resources (i.e., bandwidth, storage, and computing) to multiple tenants, thus maximizing the total revenue of the MNO and tenants.