Optimizing Dynamic Source Routing Protocol Using Computational Intelligent Approach

Wireless sensor networks have undergone significant advancements in recent decades, with research efforts focusing on areas such as routing, security, localization, deployment, and energy efficiency. One emerging trend in WSN research is the integration of Swarm Intelligence-based techniques, which have shown promise in improving efficiency, performance, robustness, and scalability. The objective of this research paper is to evaluate the performance of various existing routing protocols through simulations including DSR with the analysis of ACO routing protocol's performance in relation to routing overhead, end-to-end delay, throughput, and packet delivery rate particularly, the study focuses on comparing the performance of the DSR protocol with ACODSR. The simulation-based network simulator NS2 results and data analysis reveal that the ACO Based Routing Protocol demonstrates a significant improvement in evaluation of the ACO routing protocol's performance in comparison with existing routing protocols for wireless sensor networks. This research contributes to the ongoing exploration of swarm intelligence-based techniques in WSNs and provides valuable insights into the comparative performance of routing protocols, facilitating informed decision -making in the design and implementation of WSNs. . According to the simulated outcomes,the average performance of ACO-DSR is better than conventional DSR regarding QoS parameters like Packet delivery ratio was increased from 13.406% to 16.728% and the throughput was higher by 0.7638 mbps to 1.0812 mbps. The routing overhead was low from 2.604% to 2.012% and the AE2E delay was found low 9.754 ms. to 8.19 ms. in comparison to DSR.