QUO VADIS: QoS-aware underwater optimization framework for inter-vehicle communication using acoustic directional transducers

Abstract

Abstract-Underwater acoustic communications consume a significant amount of energy due to the high transmission power (10 − 50 W) and long data packet transmission times (0.1 − 1 s). Mobile Autonomous Underwater Vehicles (AUVs) can conserve energy by waiting for the 'best' network topology configuration, e.g., a favorable alignment, before starting to communicate. Due to the frequency-selective underwater acoustic ambient noise and high medium power absorption -which increases exponentially with distance -a shorter distance between AUVs translates into a lower transmission loss and a higher available bandwidth. By leveraging the predictability of AUV trajectories, a novel solution is proposed that optimizes communications by delaying packet transmissions in order to wait for a favorable network topology (thus trading end-to-end delay for energy and/or throughput). In addition, the solution proposed -which is implemented and compared with other solutions using an emulator that integrates underwater acoustic WHOI Micro-Modems -exploits the frequency-dependent radiation pattern of underwater acoustic transducers to reduce communication energy consumption by adjusting the transducer directivity on-the-fly.

Energy Efficiency Analysis of Effective Hydrocast for Underwater Communication

“…14 The void recovery paradigm with mechanical devices such as a floating buoy, autonomous underwater vehicles as in QUO VADIS, 15 and Depth Controlled routing 16 are not preferred due to the extra energy cost incurred by it.…”

Uncertainty-aware localization solution for under-ice autonomous underwater vehicles

“…This shift can then be leveraged to improve the performance of solutions for problems in a variety of fields. For example, in UW-ASNs, using the external-uncertainty region, routing errors can be reduced and a node can estimate better the transmission power to guarantee the Signal-to-Noise Ratio for correct data reception by taking into account not only channel impairments but also position uncertainty [4]. The notion of external uncertainty can also be used in underwater robotics to minimize the risk of vehicle collisions; and in underwater localization to decrease the position uncertainty by selecting a proper subset of nodes to be used as "references", as shown later.…”

“…Then this internal uncertainty information is broadcast for other AUVs to estimate external uncertainties. Our previous work in [4] provided a statistical solution to estimate the internal and external uncertainty, which is used for initial estimation here.…”

“…This prediction of future internal uncertainty is based on the current estimated internal uncertainty and AUV's trajectory. A solution has been proposed in [4] for underwater gliders (one type of buoyancy-driven AUVs), which we adopt in this work. As the previous optimization problem, we can also convert it into discrete variable optimization problem and solve it in a similar way.…”

“…Specifically, a position uncertainty model in [4] is introduced to characterize an AUV's position. This model is extended to estimate the uncertainty associated with the standard distancebased localization technique, resulting in the distance-based localization with uncertainty estimate (DISLU).…”