An Efficient Energy Maximization Protocol Design based on Convolutional Route Optimization Protocol

Due to its numerous possible applications, Wireless Sensor Networks (WSN) have generated an enormous amount of interest for their data collection and monitoring capabilities. Increasing the network's longevity is made difficult by the low battery life of sensor nodes. An extensive number of sensor nodes, either embedded in or physically near the monitored environment, make up a sensor network. A WSN's design and resources are limited in a way that conventional networks aren't. The processing and transmission capabilities of sensor nodes are severely lacking. Consequently, sensor networks primarily address concerns related to the longevity of the network, whereas traditional networks prioritize attaining good quality of service. Optimizing is crucial in order to accomplish this. In this paper, a new approach is presented, the Convolutional Route Optimization Protocol (CROP), which aims to maximize energy while executing error-free routing. To test how well the proposed scheme works, it is cross-validated with the conventional routing protocol, Disjoint Vector Routing (DVR). Nodes in the network can be selected as source routing nodes based on their residual energy using the proposed model. In order to keep the energy consumption of all the sensor nodes consistent, the source routing nodes choose the optimal source routing path for each shared node. Because of this, partial nodes can participate in routing. Data transmission energy usage may be further decreased by making use of the proposed optimization method's distance-based routing approach, which finds the optimal transmission path for each node globally. The appropriate graphical proof of efficiency is provided in the resulting section of this article.