Optimization of the implementation of network slicing in 5G RAN

Slicing is an emergent technology for 5G. It decomposes a single Radio Access Network (RAN) into multiple virtual networks "slices" to meet demands in term of throughput, mobility, latency, reliability, etc. Slicing needs real-time reconfigurations to keep current with demands' dynamics. This results in an increased cost of Operation Expenditures (OPEX). We approached this challenge as an optimization problem of infrastructure's resources. We virtualized and pooled Baseband Units (BBUs) resources on cloud. Dynamic allocation and interconnection with Remote Radio Heads (RRHs) are made possible by leveraging the advents of Network Function Virtualization (NFV) and Software-defined Networking (SDN). We implemented Distributed Base Station (DBS) using open software platform along to a public service orchestration tool for clouds. Our contribution is integrating service selection and deployment with real-time monitoring that allowed auto-control of resources by looping resources' lifecycle. In our experiments, we deployed several slices and we tested two scenarios. First scenario addressed slices' auto-scaling (Infrastructure Scale- Out/Scale-In) when free resources are available in the pool. Second scenario simulated slices' breathing (orchestration of resources) when the pool of resources is exhausted. In first scenario, results show that leveraging cloud elasticity by auto-scaling resources saves costs by providing exactly "what-is-needed" "when-it-is- needed" in term of cloud computing. In second scenario, results show that slices' breathing maximizes the usability by employing our "inhale-and-exhale" heuristic. It is about reusing resources from under-loaded slices in favor of overloaded ones with seamless effect on the user-experience.