Biologically Inspired Resource Allocation for Network Slices in 5G Enabled Internet of Things
The fifth generation (5G) mobile communication system is regard as a key enabler in promoting the deployment of Internet of Things (IoT) which is accompanied by the increasing service demands such like high data rate, enormous connection, and low latency. To meet these demands, network slicing has been envisioned as an efficient technology to customize infrastructures and allocate resources for 5G IoT services. However, due to various application backgrounds and ubiquitous social interactions of IoT services, the heterogeneous and social driven resource requirement of users should be carefully assessed in resource allocation for the sliced 5G wireless network. In this paper, a novel nature inspired wireless resource allocation scheme with slice characteristic perception is proposed, which comprehensively analyzes the properties of slices and converts them into a network profit model of resource utilization. Specifically, personalized service preferences and evolutionary interest relationships of users are exploited to model the complex and dynamic network environment with cellular automaton, and a biologically inspired allocation strategy of virtual wireless resource is proposed on the requirements of continuously updated user groups. Simulation results show that the proposed scheme achieves favorable resource utilization and low computational complexity, which favors the dynamic IoT slicing architecture and improves the efficiency and flexibility of resource allocation.
IEEE Internet of Things Journal