From Massive IoT Toward IoE: Evolution of Energy Efficient Autonomous Wireless Networks

Abstract

The challenge of the expansion of millions of data-intensive Internet of Things (IoT) devices has led to more restriction data rates in the 5G wireless communication network. A web server can make use of network features and functions in a variety of capacities by detecting digital records of human and object behaviors from the Internet of Everything (IoE) for autonomous networks and devices. While web server appears to be a potential option when used in conjunction with next-generation wireless communications, such as 5G technology, it introduces new issues at the edge of the network. In this article, we discuss the progression in the development of wireless technologies beyond IoT (i.e., IoE for autonomous networks), while explaining the key enabling technologies beyond 5G networks. A web server-based edge architecture has been proposed for managing a large-scale of IoE devices based on 6G-enabled technology for autonomous networks and a smart resource distribution approach. The proposed system allocates receiving work-loads from IoE devices based on their flexible service requirements using the Boltzmann machines approach designed for energy-efficient communications. In addition, at the edge network, an Artificial Intelligence (AI)-driven method, namely the Support Vector Machines (SVM) retrieval model, is used to assess the data and obtain accurate results. The proposed system has been simulated and compared with some of the existing algorithms considering different use case scenarios. An overview of the emerging challenges of the proposed architecture has been discussed.