Biologically Inspired Resource Allocation for Network Slices in 5G-Enabled Internet of Things

TLDR

5G is a key enabler for IoT, promising high data rates, massive connectivity, and low latency, but the heterogeneous, socially driven resource demands of IoT services require careful assessment in network slicing. The authors propose a nature‑inspired wireless resource allocation scheme that perceives slice characteristics and transforms slice properties into a network profit model of resource utilization. The scheme models personalized service preferences and evolutionary user relationships with a cellular automaton and applies a biologically inspired strategy to allocate virtual wireless resources to continuously updated user groups. Simulations demonstrate that the scheme achieves high resource utilization, low computational complexity, and enhances the efficiency and flexibility of dynamic IoT slicing.

Abstract

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.