A WSN is a network of sensor nodes that track and record the status of the physical atmosphere and organize the gathered data in a central location. WSNs' technology is employed as the basic infrastructure of the Next Generation Networks (NGN) including Internet of things (IoT), Sensor Control Networks (SCNs), Ubiquitous Sensor Networks (USNs), Machine-Oriented Communications (MOC) and so on. To control the network energy dissipated and to minimize traffic and overhead during data transmission phases, an energy-efficient routing protocol is necessary to fulfill the sensing, communication and processing tasks of WSN. Clustering is used strategy for balancing energy consumption across all sensor nodes (SN) in network. As a clustering-based routing protocol (RP) for WSN, this paper presents an ensemble bio-inspired procedure based on the Firefly and Spider Monkey Optimization (SMO) algorithms. By recycling frequent information from the source node into the sink, the proposed protocol avoids superfluous routing messages, which may result in significant energy waste. This routing protocol can select the best routing path. To pick the appropriate cluster heads at each round, the proposed algorithm used various parameters such as node residual energy, inter-cluster distances to the sink, and cluster overlaps. In the clustering process, the parameters of the projected solution can be adaptively optimized to attain the finest performance of the network necessities. Simulation results have showed average lifetime enhancements of up to 30.91%, 32.12%, 12.4%, 13.50% compared with bee colony, PSO, SFLA and GWO respectively, in different network scenarios.