The sensor nodes sense an event and report to the nearest base station for respective action. There are various applications of WSN where sensor nodes are deployed in an infrastructure-less network. Due to the short communication range of sensor nodes, the intermediate nodes collaborate in forwarding the data packets. After a lot of advancement in wireless sensor networks, it is lacking with few specifications like limited memory, inadequate computation, limited bandwidth, and battery-powered nodes. The sensor nodes of the wireless sensor network (WSN) sense the data or event, gather the data under defined infrastructure, and process the received signals. The deployment of sensor nodes is application-dependent, so it can be random or deterministic. The sensor nodes can be deployed in all accessible and inaccessible areas for sensing the data across various applications like battlefield, building inspection, target field imaging greenhouse, and monitoring disaster area. The advancement in low-cost, small, and tiny sensor nodes makes a significant role where the sensor nodes have very attractive characteristics of sensing the environmental conditions and process the received signals. Finally, the simulation result presents that the proposed approach outperforms the state of the art approaches in terms of average energy consumption, delay, and throughput and packet delivery ratio. Huffman coding considers the packet loss rate on different alternate paths discovered by ant colony optimization for selection of an optimal path. The forward ant constructs multiple congestion-free paths from source to sink node, and backward ant ensures about the successful creation of paths moving from sink to source node, considering energy of the link, packet loss rate, and congestion level. Specially, ant colony optimization has been employed to find multiple congestion-free alternate paths. This approach is a combination of traffic-oriented and resource-oriented optimization. To tackle all the mentioned issues, this paper proposes an efficient congestion avoidance approach using Huffman coding algorithm and ant colony optimization (ECA-HA) to improve the network performance. Routing is one of the most preferred approaches for minimizing the energy consumption of nodes and enhancing the throughput in WSNs, since the routing problem has been proved to be an NP-hard and it has been realized that a heuristic-based approach provides better performance than their traditional counterparts. The consequence of this turns in to overflowing of the buffer at each receiving sensor nodes which ultimately drops the packets, reduces the packet delivery ratio, and degrades throughput of the network, since retransmission of every unacknowledged packet is not an optimized solution in terms of energy for resource-restricted sensor nodes. Congestion in wireless sensor networks (WSNs) is an unavoidable issue in today’s scenario, where data traffic increased to its aggregated capacity of the channel.