AI-Assisted Energy-Efficient and Intelligent Routing for Reconfigurable Wireless Networks
Dingde Jiang, Zhihao Wang, Wenjuan Wang, Zhihan Lv, Kim‐Kwang Raymond Choo
Abstract
Intelligent network management for reconfigurable wireless networks such as 5G and beyond applications is crucial for many industrial applications, and has been the subject of ongoing research. This paper proposes an Artificial Intelligence(AI)-Assisted energy-efficient and intelligent routing, based on both energy efficiency prioritization and AI theory, in order to meet the exacting demands particularly in a real-world scenario. Specifically, to achieve network intelligence and quality of service (QoS), we use the AI theory to enhance routing adaptivity for intelligent network management in reconfigurable wireless networks. The software-defined networking idea is used to achieve this goal from a network-level perspective. To facilitate self-awareness, self-study, self-decision making, and self-configuration, we construct a mathematical model to convert the energy-efficient and intelligent routing problem into a multi-constraint optimal problem. Then an AI-assisted intelligent routing algorithm is designed to dynamically and adaptively change link weighs, which allows us to achieve optimal energy efficiency. Findings from our simulation suggest the potential of our proposed approach.