Hybrid Optimization Algorithm for Reliable Routing in Wireless Sensor Network

In Wireless Sensor Networks (WSN), congestion is a major problem as data traffic increases to the channel’s aggregate capacity. Routing is one of the best methods for reducing node energy usage and increasing throughput in WSNs. This research suggests an effective congestion avoidance strategy based on the Huffman coding technique and Forward Error Code (FEC) integrated with a metaheuristic optimization algorithm to enhance network performance. Using a hybridization of the traditional Zebra Optimization Algorithm (ZOA) and Harris Hawk Optimization (HHO) techniques, the proposed Zebra Hunt Optimization (ZHO) algorithm determines the optimal best paths for sharing the data packet. This process determines the best path for routing the data packet. Here, selection is based on fitness parameters such as flow-based features, buffer occupancy, bandwidth, and throughput. Then, the link quality estimation is evaluated for the identified optimal best path. Also, including a coding scheme in the data packet corrects the errors in transmitted data without retransmission and reduces redundancy.