Design of Artificial Intelligence Enabled Dingo Optimizer for Energy Management in 6G Communication Networks

Abstract

The sixth-generation (6G) networks offer effective results over the earlier generations for satisfying the needs of emergent services as well as applications like multi-gigabit transmission rate, high reliability, delay, and ubiquitous connections for Internet of Everything (IoE). But due to the shortage of spectrum resource, effectively managing the resources are essential in accomplishing promising needs. One of the proficient ways of achieving maximum energy management is cluster based routing process. In this view, this paper presents an artificial intelligence enabled dingo optimizer for energy management (AIDO-EM) in 6G networks. The presented AIDO-EM technique involves the major goal of minimizing the energy utilization and maximizing the lifetime of the 6G enabled Internet of Things (IoT) devices. For accomplishing this, a new dingo optimization algorithm (DOA) is applied for cluster enabled routing to achieve effective data distribution among the devices and choose effective gateway heads (GWH). In order to demonstrate the enhanced outcomes of the AIDO-EM technique, a series of simulations were carried out and the results reported the enhanced performance over its recent state-of-art approaches.