Zero-Knowledge Neighbor Discovery for Underwater Optical Wireless Sensor Networks

Yu Tian, Lei Wang, Chi Lin, Bin Han, Lupeng Zhang, Zhiyi Zhou, Yu Sun, Bingxian Lu

Abstract: Neighbor discovery poses significant challenges in Underwater Optical Wireless Sensor Networks (UOWSNs) due to the unique characteristics of directional transceivers, line-of-sight communication, and mobility induced by water currents. Traditional methods typically rely on prerequisites and prior knowledge, such as centralized coordination, time synchronization, and neighbor-related information, which are often unavailable or impractical in underwater environments. In this paper, we make the first attempt to address the issue of Robust and Efficient Neighbor Discovery (termed the REND problem) in UOWSNs with zero-knowledge. Here, zero-knowledge refers to the capability that enables sensors to identify neighbors in dynamic underwater optical channel conditions without prerequisites or prior knowledge. We design a zero-knowledge distributed directional neighbor discovery scheme inspired by gear meshing. We then propose a deterministic algorithm for the REND problem based on theoretical analysis. Additionally, to further reduce the discovery delay for the periodic REND problem, we develop a greedy-based approximation algorithm with a performance guarantee. Finally, extensive simulations demonstrate that the proposed scheme reduces the discovery delay by 34.9% on average and achieves an additional 54.4% reduction for periodic neighbor discovery. Furthermore, test-bed experiments are carried out to verify the applicability of our zero-knowledge scheme in real-world scenarios.

External IDs:dblp:journals/tmc/TianWLHZZSL25