Research in Delay Tolerant Networks (DTNs) focuses on ensuring reliable data delivery in environments with intermittent connectivity, high latency, and dynamic topology. Recent studies introduce adaptive and intelligent routing protocols that utilize buffer management, message replication, and probabilistic forwarding to improve delivery rates and reduce delays. Machine learning and deep reinforcement learning approaches are increasingly applied to predict contact opportunities, optimize routing paths, and manage network resources efficiently. Energy-aware and security-enhanced DTN architectures are also being developed to address challenges in heterogeneous and resource-constrained networks. Furthermore, blockchain-assisted and edge-enabled DTNs are emerging to provide trust, accountability, and faster data dissemination. These advancements collectively enhance the performance, scalability, and reliability of DTNs in challenging scenarios such as disaster recovery, vehicular networks, and space communications.