Abstract:
5G networks will support many new services and applications with diverse QoS requirements like high data rates and low E2E latency. Moving computation to the network edge reduces E2E latency.
However, edge nodes have limited computational resources, making QoS requirements difficult to meet. We use mixed-integer linear programming (MILP) to solve a joint user association, service function chain (SFC) placement, where SFCs are composed of virtualized service functions (VSFs), and resource allocation problem in 5G networks with DUs, CUs, and a core network (5GC).
We compare four problem-solving methods. The first two methods reduce user E2E latency and service provisioning cost. The other two minimize VSF migrations and their impact on user experience, while the last one reduces inter-CU handovers. We then propose a heuristic to address MILP-based solution scalability. Simulations prove the heuristic algorithm works.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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