Dynamic Resource Optimization Allocation for 5G Network Slices Under Multiple Scenarios
Shanbin Li, Qifan Hu · 2020
The significant improvement of 5G technology will be a huge driving force for the Internet of Things (IoT). Furthermore, the concept of network slice provides the possibility of customization for IoT applications. How to optimize resource allocation in multiple scenarios has become a challenge we are facing. In this paper, we propose a bandwidth resource's dynamic allocation scheme which is suitable for both Enhance Mobile Broadband (eMBB) scenario and Ultra Reliable and Low Latency Communication (uRLLC) scenario. Based on the classical Software Defined Network (SDN) architecture, admission control is introduced to maintain the resource utilization of the network, and the delay penalty factor we set can guarantee the low delay of the network. Besides, we make a tradeoff between the benefit and the cost of network when adjusting resources. Simulation results show that the algorithm can meet the performance requirements of different application scenarios while minimizing the cost of dynamic resource adjustment.