Comprehensive Literature Review on Bio Inspired Optimization-based Path Selection for Message Forwarding in Delay Tolerant Network

Delay Tolerant Network (DTN) is suitable to work in extreme conditions where traditional networks failed to establish path between nodes, this paper seeks to offer a thorough examination of the use of bio-inspired optimization methods for path selection and message forwarding in DTNs. The paper examines the efficacy of three algorithms Genetic Algorithms (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO) in improving message forwarding in difficult DTN environments with erratic delays and sporadic connectivity. By means of a thorough examination of existing literature and practical trials employing actual DTN traces, the study unveils noteworthy advancements attained by bioinspired optimization techniques. In terms of resource usage, adaptability to changing network conditions, and message delivery efficiency, GA, ACO, and PSO show encouraging outcomes. The comparison study clarifies the advantages and disadvantages of each method, providing practitioners, researchers, and network designers with insightful information. The study's practical significance is further enhanced by the validation of these bio-inspired methodologies using real-world DTN traces, which serves as a link between theoretical developments and practical application. This paper provides a practical guide for using bio-inspired optimization in DTNs by identifying optimal configurations and recommended practices. The results have broad implications for a variety of scenarios, such as disaster recovery, communication in space, and remote locations.