<p>Internet of things (IoT) applications are witnessing an exponential rise in present times; this network of things always requires a wireless sensor network (WSN) to operate as a support system, where the sensors will sense and send collected data for further application-specific action. Past studies have highlighted that in such sensor networks, the limited battery of sensors is one of the most significant issues, and clustering protocols have been proposed by various researchers as a solution to overcome this issue. However, selecting a cluster head (CH) optimally is still an area of ongoing research. The primary objective is to reduce energy consumption and increase network lifetime. This paper proposes a solution to select CH based on two newly proposed parameters: the optimized lifespan of the sensor and variation in the density of the local neighborhood. These two parameters reflect the fitness of the node to become a CH; this process of selection is then optimized using a combination of firefly and cuckoo search (FCS) optimization algorithms. The simulations were conducted in MATLAB, and network performance was analyzed in terms of the remaining energy in the network, stability period, and network lifetime. The proposed protocol was compared with other state-of-the-art schemes, and it was observed that the proposed protocol outperformed the others by an acceptable margin. The network stability period and lifetime have witnessed a significant improvement due to the optimal CH selection process.</p>