Hybrid Fuzzy Data Aggregation and Optimization-Based Routing for Energy Efficiency in Heterogeneous Wireless Sensor Networks

Wireless sensor networks (WSNs) are networks with many sensor nodes that are utilized for various purposes, including the military and medical. In hazardous circumstances, precise data aggregation and routing are essential, and the energy consumption of the sensors needs to be closely controlled. Nonetheless, there is a significant chance of redundant data because of external factors and nearby sensors. A multitude of information can be found in large datasets, some of it unnecessary and others useful. This redundancy negatively impacts performance in terms of redundant transmission and computing costs. However, data aggregation might help a network get rid of unnecessary data. In this work, we present a hybrid protocol called fuzzy data aggregation with fuzzy spider monkey optimization routing protocol (FDA-FSMORP) that represents an intelligent approach to collecting sensor data in HWSNs considering energy consumption. The results indicated that the suggested method beat in minimizing data latency our approach reduced energy consumption by 73% using energy more effectively when compared to our simulated outcomes