Efficient Resource Management for IoT Devices in Mobile Networks Using Packet Collection and Forwarding in Transportation Systems

Abstract

The Internet of Things (IoT) and Machine Type Communication (MTC), also known as Machine-to-Machine (M2M) communication, have led to significant advancements in various industries, resulting in a notable increase in IoT devices in recent years. A range of communication technologies, including Low Power Wide Area Networks (LPWAN), Narrow Band IoT (NB-IoT), Long-Term Evolution (LTE), LTE-Advanced (LTE-A), and emerging 5G & 6G cellular networks, have been deployed to connect IoT sensors and devices. LTE and LTE-A are particularly effective for IoT device interoperability due to their widespread availability. However, the current cellular mobile networks are primarily designed to cater to broadband services and human-based communication (H2H), which poses challenges for handling the narrowband traffic generated by IoT devices, especially when millions of devices communicate within a single cell, such as during transportation. In transportation systems, where containers carrying various goods require continuous data transmission, this massive volume of IoT traffic can overwhelm network resources, leading to inefficient spectrum usage. This paper proposes an innovative solution to address these challenges by introducing a resource management framework that utilizes packet collection and forwarding techniques. Specifically, the system employs an intermediary node, termed the Packet Collection and Forwarding (PCF) node, which temporarily stores small packets in a buffer. Once the buffer reaches capacity, these tiny packets are aggregated into a larger packet and forwarded to the recipient, reducing network congestion and enhancing resource allocation efficiency. Additionally, the system incorporates strategies to minimize delays in the micro-packet collection process, ensuring minimal impact on communication latency. By leveraging this approach, the proposed system optimizes network performance, reduces energy consumption, and supports scalable, sustainable IoT solutions in mobile networks, particularly in transportation systems. Simulation results demonstrate significant improvements in resource management, throughput, and overall network efficiency, contributing to the development of robust IoT infrastructures for dynamic environments.