The wireless sensor network (WSN) contains a huge number of cost-effective and small energy-constrained nodes for network communication. Moreover, the clustering is considered as a major part of WSNs routing. Hence, this paper develops the Cosine Lotus Effect Algorithm (CLEA) for Cluster Head (CH) selection, and the Fractional Cosine Lotus Effect Algorithm (FCLEA) for routing. Initially, the network simulation is carried out, and the CH is done using the proposed CLEA with the fitness components such as Link Lifetime (LLT), delay, inter, and cluster distance, trust factor, and energy, in which, the Radial Basis Function Network (RBFN) is employed for energy prediction. The proposed FCLEA is utilized for routing, where fitness factors such as energy, delay, distance, and trust factors are utilized. Moreover, the FCLEA-based routing obtained the better average residual energy, distance, and throughput of 1.719 J, 7.068m, and 431.8.