CAREER: Investigating Fundamental Problems for Underwater Multimedia Communication with Application to Ocean Exploration

Wireless acoustic communication is the typical physical-layer technology underwater because of the high medium absorption of radio frequencies and of the scattering problem affecting optical waves. As of today, however, acoustic communication solutions support only delay-tolerant low-bandwidth monitoring applications. Conversely, this research enables near-real-time acquisition and processing of heterogeneous data from mobile and static ocean exploration platforms. Reaching this goal will improve the efficiency of monitoring key dynamic oceanographic phenomena such as phytoplankton growth and rate of photosynthesis, salinity and temperature gradient, and concentration of pollutants. Toward this end, this research studies underwater inter-vehicle communication solutions aimed at enhancing the capabilities of the NSF's Ocean Observatories Initiative (OOI) cyberinfrastructure. The primary intellectual merit of this project offers the distinction between two forms of position uncertainty. Typically, uncertainty in the position of a mobile vehicle as estimated in relation to itself (which the PI refers to as internal uncertainty) is the focus of distributed underwater robotics and networking. By contrast, the PI introduces the new notion of external uncertainty, in which uncertainty in the position of a mobile vehicle is estimated by others. Specifically, this project focuses on modeling external uncertainty, on designing reliable underwater communication solutions that exploit the external-uncertainty notion, and on demonstrating the effectiveness of integrating computation and communication resources on marine science and technology through emulations and field experiments. One of the broader impacts of this work is the generation of computer-literate undergraduate and graduate researchers with a comprehensive knowledge in underwater sensing, communication, and coordination. The PI will create new teaching modules on distributed sensing, provide opportunities for exchange programs, leverage existing minority student outreach networks at Rutgers, and incorporate student exchange programs as well as team-teaching approaches.