Abstract
Underwater wireless acoustic sensor networks (UWASNs) have emerged as a powerful communication technology for discovering and extracting data in aquatic environments. UWASNs have numerous applications in areas such as fisheries, resource exploration, mine reconnaissance, oil and gas inspection, marine exploration and military surveillance. However, these applications are limited by the capacity of networks to detect, discover, transmit, and forward big data. In particular, transmitting and receiving large volumes of data requires great lengths of time and substantial power, and thus fails to meet the real-time constraints. This problem has motivated us to focus on developing an underwater computer-embedded system capable of efficient big-data management. Thus, we have developed methods to discover and extract valuable information beneath the ocean using data-mining approaches. Previously, we introduced real-time underwater system architectures (RTUSAs) that use a single computer. In this study, we extend our results and propose a new RTUSA for large-scale networks. This novel RTUSA uses multi-computers and aims to enhance the reliability of our proposed system. Determining the optimal location of computers with respect to their membership of acoustic sensor nodes, so as to minimize delay time, power consumption, and balance loads, are NP-hard problems. Therefore, we propose a heuristic approach that enables optimization of computer locations and their memberships of acoustic sensor nodes. We conduct simulations to show the merits of our findings and measure the performance of our proposed solution.