Energy Aware Routing Protocol with Data Fusion and Machine Learning

Abstract

The current wireless and communication system may be attributed to the contributions made by the Sensor Network in a significant measure. During the last decade, several efforts have been performed to examine and propose answers to challenges about the energy efficiency of wireless sensor network communications. Several different researchers has done these efforts. The challenge of constructing economical energy-use paths has not yet been overcome. Because sensors have limited computational capabilities, which are frequently coupled with energy limitations, it is rather difficult to guarantee that a sensor’s lifespan will be longer. This is because of the energy constraints often associated with these limitations. The results of this research have led to the development of a one-of-a-kind communication system for sensor networks that is not only environmentally friendly but also supported by three distinct revolutionary frameworks. The framework that has been recommended, which goes by the name Potential Energy Efficient Data Fusion (PEE-DF), is the one that is in charge of the optimization of energy. It achieves this with the aid of probabilistic approaches and clustering. The K-SOM (Korhonen self-organizing map) framework was designed using a globular topology, which aids load balancing during data fusion. K-SOM stands for Korhonen self-organizing map. This was done to ensure we got the most out of our resources. A novel method to routing is presented by the technique, which has the potential to be used to assist in the operation of energy-efficient routing in large-scale wireless sensor networks. The framework for the Tree-Based Fusion Technique (TBFT), which has been offered, comes up with a new way for dynamic reconfiguration. This is accomplished via the introduction of the concept of routing agents. The strategy enables the system to recognise which sensor has a greater energy dissipation rate and then instantly moves data fusion work to a more energy-efficient node. This allows the system to save energy. This approach, based on thresholds, enable a sensor to act as a cluster head up until it reaches its threshold remnant energy and then as a member node once it exceeds threshold residual energy. In other words, it may play both roles simultaneously. It is possible to fulfil both of these responsibilities at the same time. The findings have been mathematically modelled using a standard radio-energy model, which has enhanced the robustness of the findings, which is highly positive. The results were encouraging because of the increased robustness of the findings. Compared to the benchmark previously established for energy-efficient strategies, the proposed system demonstrates higher performance in terms of its ability to communicate while using less energy. In contrast to LEACH, the recommended system's findings reveal an almost fifty percent decrease in energy consumption, and at the same time, a reduction in the amount of time required to carry out the operation..