Research in cyclic Mobile Ad Hoc Networks (MANETs) focuses on optimizing communication reliability, energy utilization, and routing efficiency in network topologies where nodes move or communicate in repetitive or cyclic patterns. Recent studies propose mobility prediction models and time-aware routing protocols that leverage the cyclic behavior of nodes to enhance connectivity and data delivery. Machine learning and graph theory–based approaches are employed to identify recurring movement patterns and optimize link scheduling and cluster formation. Energy-efficient and delay-tolerant communication strategies are also introduced to minimize transmission overhead while maintaining stable routes. These advancements enable more predictable, reliable, and resource-efficient networking in cyclic MANET environments.