Multivariate weighted isotonic regressive modest adaptive boosting-based resource-aware routing in WSN

WSN includes a scenario where many sensor nodes are distributed to monitor environmental conditions with route collected data toward sinks via the internet. WSNs efficiently manage the broader network with available resources, such as residual energy and wireless channel bandwidth. Therefore, a routing algorithm is essential to enhance battery-constrained networks. Many existing techniques are developed for balancing energy consumption, but the efficient routing was not achieved. The multivariate weighted isotonic regressive modest adaptive boosting-based Resource-Aware Routing (MWIRMAB-RAR) technique is introduced to enhance routing. The MWIRMAB-RAR technique includes a different process, namely resource-aware node selection, route path discovery, and data transmission. Initially, the MWIRMAB-RAR technique uses the modest adaptive boosting technique uses the multivariate weighted isotonic regression function for detecting resource-efficient sensor nodes for effective data transmission. After that, multiple route paths are established based on the time of flight method. Once after showing a route path, the source node sends data packets to the sink node via resource-efficient nodes. The data delivery was enhanced and minimized packet loss as well as delay. The simulation analysis is carried out on certain performance factors such as energy consumption, packet delivery ratio, packet loss rate, and delay with several data packets and sensor nodes. The obtained evaluation indicates that MWIRMAB-RAR outperforms well in increasing data packet delivery and reducing energy consumption, packet loss rate, and delay.