Predictive Model Techniques with Energy Efficiency for IoT-Based Data Transmission in Wireless Sensor Networks

Abstract

Wireless sensor networks are limited by the vast majority of goods with limited resources. Power consumption, network longevity, throughput, routing, and network security are only a few of the research issues that have not yet been addressed in sensor networks based on the Internet of Things. Prior to becoming widely deployed, sensor networks built on the Internet of Things must overcome a variety of technological obstacles as well as general and specific hazards. In order to address the aforementioned problems, this research sought to improve rogue node detection, reduce packet latency/packet loss, increase throughput, and lengthen network lifetime. Wireless energy harvesting is suggested in the proposed three-layer cluster-based wireless sensor network routing protocol to extend the energy lifespan of the network. For the purpose of recognising and blacklisting risky sensor node behaviour, a three-tier clustering architecture with an integrated security mechanism is suggested. This clustering approach is cost-based, and the sink node selects the cluster and grid heads based on the cost function’s value. With its seemingly endless potential across a wide range of industries, including intelligent transportation, the Internet of Things (IoT) has gained prominence recently. To analyse the nodes and clustering strategies in IoT, the suggested method PSO is applied. A plethora of new services, programmes, electrical devices with integrated sensors, and protocols have been produced as a result of the Internet of Things’ explosive growth in popularity.

RETRACTED: Enhanced Swarm Distributed Energy-Efficient Clustering Method for IoT Network Using Crossbreed Optimization Methods

“…The authors propose the Spanning Tree-Based Flooding Mechanism with Cooperative Game Theory (STBFM-CGT) as a secure data communication method for IoT-WSN networks, balancing energy consumption and security.The proposed method reached efficient data transmission in IoT-WSN networks that achieve better results as compared to advanced methods. R. Bharathi et al (2022) [12] described that WSN Wireless sensor networks face limitations due to limited resources, including were not yet addressed in the IoTs. The authors proposed a model to enhance rogue node detection in IoT sensor networks before widespread deployment.…”

Neural Network-Based Soil Parameters Predictive Coordination Algorithm for Energy Efficient Wireless Sensor Network

“…This approach can improve the energy efficiency of the algorithm because it reduces the amount of time the sensors are active, while still providing accurate predictions of soil parameters. To explain this By turning off the sensors periodically and using the RNN to predict soil parameters, the Idle Energy Consumption can be increased, which in turn decreases the Total Energy Consumption [13]. The RNN can be used to predict the values of soil parameters at each time step, and the sensors can be turned Neural Network-Based Soil Parameters Predictive Coordination Algorithm for Energy on only, when necessary, based on the predicted values.…”

Combined localization and clustering approach for reduced energy presumption in heterogeneous IoT

“…Heterogeneous WSNs, featuring sensor nodes with varied capabilities, have garnered attention for their adeptness in tackling the complexities of modern IoT applications (Aziz et al 2020). While existing research has largely focused on heterogeneous WSNs, limitations persist in heterogeneous setups, including battery constraints, processing capacity, and versatility (Bharathi et al 2022). Consequently, these constraints impede sustained operations and adaptability to changing environments.…”