Wireless sensor networks involve small sensor nodes equipped with sensing, processing, and communication abilities. Clustering is widely acknowledged as an effective method for optimizing data transmission efficiency in such networks. In this research, an Enhanced Agglomerative Hierarchy Algorithm based on Low-Energy Adaptive Clustering Hierarchy (EAHA-LEACH) has been proposed, combined with an enhanced time-controlled jellyfish optimization algorithm, improves network lifetime by selecting the optimal cluster head from a candidate pool. The proposed model is implemented using NS3 tool. Finally, while comparing with existing techniques, the introduced hybrid clustering-based LEACH protocol achieved better initial throughput (5800 bits/s) and responded fine by 3500 rounds, energy consumption (100 J) for 240 rounds, 98% alive nodes till 250 rounds, dead node ratio as 2%, residual energy as 52 J, communication overhead as 4%, network delay (0.039 s), latency (1 ms), and network lifetime (1700s).