An Energy-aware Technique for Resource Allocation in Mobile Internet of Thing (MIoT) Using Selfish Node Ranking and an Optimization Algorithm

Abstract

Internet of Things (IoT) is a new revolution of the Internet, which can be thought of as an uprising expansion of internet services. IoT is defined in many different ways. It covers many areas of life, including houses, cities, automobiles, and roads. It also includes devices that track people's behavior and utilize the information gathered for push services. Any object may access the web over a wired or wireless network with the IoT. In addition to authentication and security, extensive research and development have gone into energy awareness. Mobile Internet of Things (MIoT) is the following stage in this situation. Mobile data collecting, data analysis, energy management, security and privacy, and the provision of IoT services are some issues arising when using MIoT. So, this paper proposed an energy-aware technique for resource allocation in MIoT. Due to this problem's NP-hard nature, a new approach is suggested to reduce the network's energy consumption and end-to-end delay in MIoT using selfish node ranking and ant colony optimization algorithms. The proposed method is compared to Whale Optimization Algorithm (WOA) and Task Priority-based Resource Allocation (TPRA) algorithms. The findings show the network's substantial changes in energy consumption and end-to-end delay using the proposed method. The findings of the current work are significant for academics and offer insights into upcoming study areas in this subject.