Enhanced Clustering MAC Protocol Based on Learning Automata for UV Networks

Abstract

Ultraviolet (UV) networks are widely applied in complex electromagnetic environments. Designing an efficient multi-node medium access control (MAC) protocol for these networks is important. In this study, we proposed an enhanced clustering time division multiple access (TDMA) MAC protocol based on clustering and learning automata (LA). Subsequently, the effects of the network topology, class of service, and number of cluster nodes on the network performance under the proposed protocol were analyzed. Then, the protocol was compared with the TDMA protocol and clustering system. Results revealed that it obtained a better network performance, proving its suitability for multi-node UV networking.