Efficient communication protocols for underwater acoustic sensor networks.

摘要

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, and mine reconnaissance. The enabling technology for these applications is acoustic wireless networking. UnderWater Acoustic Sensor Networks (UW-ASNs) consist of sensors and Autonomous Underwater Vehicles (AUVs) deployed to perform collaborative monitoring tasks. The objective of this research is to explore fundamental key aspects of underwater acoustic communications, propose communication architectures for UWASNs, and develop efficient sensor communication protocols tailored for the underwater environment. Specifically, different deployment strategies for UW-ASNs are studied, and statistical deployment analysis for different architectures is provided. Moreover, a model characterizing the underwater acoustic channel utilization efficiency is introduced. The model allows setting the optimal packet size for underwater communications. Two distributed routing algorithms are proposed for delay-insensitive and delay-sensitive applications. The proposed routing solutions allow each node to select its next hop, with the objective of minimizing the energy consumption taking the different application requirements into account. In addition, a resilient routing solution to guarantee survivability of the network to node and link failures in long-term monitoring missions is developed. Moreover, a distributed Medium Access Control (MAC) protocol for UW-ASNs is proposed. It is a transmitter-based code division multiple access scheme that incorporates a novel closed-loop distributed algorithm to set the optimal transmit power and code length. It aims at achieving high network throughput, low channel access delay, and low energy consumption. Finally, an efficient cross-layer communication solution tailored for multimedia traffic (i.e., video and audio streams, still images, and scalar sensor data) is introduced.