Hybrid Underwater Localization Communication Framework for Blockchain-Enabled IoT Underwater Acoustic Sensor Network

In IoT-based underwater acoustic sensor networks (IoT-UASNs), critical challenges, such as inadequate node authentication mechanisms, unpredictable network topology, and ineffective localized node identification significantly hinder network performance. These challenges adversely impact node localization, route requests (RREQs) reconstruction at the beacon level, and lead to increased routing overhead, end-to-end delays, and unreliable data forwarding, thereby compromising underwater communication in critical areas of interest. Achieving reliable and efficient data transmission to sonobuoys while maintaining an optimal packet delivery ratio for localized nodes remains a significant priority. However, existing communication schemes often overlook the importance of authentication mechanisms, such as blockchain, in ensuring secure and efficient localization. Although previous research has focused mainly on generic localization strategies, the role of beacon-based localization, a key component in the formation of underwater networks, has been largely neglected. Despite the potential integration of beacon nodes with emerging technologies, such as blockchain, uncertainties persist about their ability to ensure secure underwater localization. This article addresses the pressing need to enhance the localization framework in AODV-based underwater networks by improving data delivery, optimizing RREQ and RREP processes, and minimizing both end-to-end delays and localization errors, thus paving the way for more reliable and secure underwater communication systems. In order to address these challenges, we first introduce a hybrid underwater localization communication framework based on the use of blockchain technology along with the proposed scheme, which is geomatric distance-based communication-based localization routing (CGDBLR). To establish the performance of this framework, we employ various node configurations and speeds with comparative experiments with state-of-the-art techniques. Our results show significant performance improvements for multiple parameters when integrating the blockchain in this context.