| Because of our limited knowledge of the huge water body that covers 70% of Earth's surface, Underwater Acoustic Sensor Network (UWASN) is an emerging topic in the research society. However, the unique properties of acoustic communication systems, such as high propagation delay, high communication power consumption, low transmission rate, distance dependent bandwidth, all make the networking issues of UWASN very challenging. In this thesis, we study three different topics that can be applied in UWASN, with a focus on addressing the challenge of high propagation delay. One is time synchronization, another one is link scheduling, and the last one is random access.Because of high propagation delay, time synchronization protocols which are designed for terrestrial-RF networks may not be suitable for UWASN. We perform extensive analysis of existing solutions, and conclude their pros and cons. Based on our findings, we propose a hybrid synchronization scheme, which outperforms existing solutions in terms of precision, has bounded multi-hop error, and low variance. In addition, we also analyze the proposed solution with other schemes in multi-hop settings. The performance of hybrid scheme is not only analyzed theoretically, but also verified by traced-based simulations.In the second topic, we formally prove the NP-hardness and best possible approximation ratio for Metric Underwater Scheduling problem. We then use a complete SAT solver to study the feasibility of a given scheduling length, regarding a network under consideration. We notice that UWASN has good throughput when the deployment density is low, but deteriorates when density goes up.Due to the inflexibility and high communication power consumption of centralized schedulers, we finally study the performance of a ALOHA-like random access scheme. We use non-linear programming to improve its throughput by modifying the channel access distribution. Based on our findings, the improvement can be several orders compared to primitive solutions. While packet length increases, schedule length decreases, and deployment density increases, the improvement ratio also goes up accordingly. |
