Multilevel Routing for Data Transmission in Internet of Things

This paper presents an improved Virtual Grid-Based Dynamic Routes Adjustment (VGDRA) algorithm for energy-efficient routing in Wireless Sensor Network (WSN)-based Internet of Things (IoT) systems. The primary objective is to optimize energy consumption while maintaining reliable data transmission. We evaluate the proposed model using machine learning techniques, including Logistic Regression, Decision Trees, Random Forest, and Boosting algorithms. Performance metrics such as accuracy, F1-score, precision, recall, and ROC-AUC score demonstrate the effectiveness of our approach. The simulation is conducted using NS2/NS3, and comparative results confirm the superiority of the improved VGDRA over traditional methods. The term “internet of things” describes a dispersed network that helps sensor nodes join or leave the network based on their needs. Due to their modest size, these nodes are placed in remote locations. As a result, the Internet of Things is experiencing an energy consumption (EC) problem. The data is transmitted across several sensor nodes (SNs) by means of the base station (BS). Similarity between data from different SNs is identified and eliminated in order to carry out the decision-making process. Additionally, the sink node is in charge of using the data locally and sending it over long distances to other network locations. In order to extend the network's lifespan, the previous work implemented an EEP (energy efficient protocol) named VGDRA. The objective of this work is to improvise the VGDRA algorithm for energy-favourable routing in WSN based IoT systems. The updated VGDRA protocol presented in this study makes use of cache nodes and takes cluster heads (CHs) into account when sending data to cache nodes. In order to assist in collecting data from sensors, the sink node is shifted closer to the cache. The recommended approach is simulated using MATLAB. Indicators such as the quantity of packets transmitted inside the network, the number of dead motes, and the number of surviving motes exhibit a 15% improvement when the enhanced VGDRA model is evaluated in comparison to the original VGDRA protocol. The updated VGDRA protocol performs noticeably better, especially when it comes to prolonging the network's service period.