Wireless Sensor Networks (WSN) are expected to transform the way data is collected, processed, and disseminated in a variety of contexts and applications. Extending the life of wireless sensor networks requires the capacity to properly manage resources (WSNs). Clustering sensor nodes with the task of improving traffic demands in the networking is a sensible method for WSN's long-term energy use.For Wireless Sensor Networks, the current system established a Hierarchical Energy-Balancing Multipath routing protocol (HEBM). However, because the sensor nodes rely on energy for their operations, if one node fails or a link breaks owing to its limited battery life, it will have an impact on the entire network, necessitating cautious resource management. And also need efficient cluster head selection scheme to improve energy efficiency. To address this issue, the suggested system created a Fault Tolerance based Energy Efficient Routing (FTEER) mechanism that provides significant energy and network lifespan gains. At randomization, sensor nodes are dispersed in a capture zone.Then use neighbour discovery to locate the nodes that are closest to you. At least one neighborhood is performed by each node in the network. In this proposed work, distance-based clustering is performed. Then optimal CH selection is done by using Adaptive Adjustment step strategy-based Glowworm Swarm Optimization algorithm (AAGSO). The proximity seen between node and the base station, the based on residual energy of the node as well as its neighbours, and the quantity of node neighbours are all considerations to consider while choosing a CH. Finally, the cluster head creates a TDMA schedule, which gives a time window for data delivery to sensor nodes.When a defect (node or connection failure) occurs during packet delivery, communication is restarted by selecting backup routes or backup nodes. With respect to packet delivery ratio, end-to-end latency, energy consumption, and average remaining round, the experimental findings reveal that the suggested system outperforms the prior systems.