A cross layer UWSN architecture for marine environment monitoring

Underwater sensor networks (UWSN) transpires as a powerful technique in marine monitoring that includes various applications such as oceanographic data collection, marine surveillance and pollution detection. Localization in UWSN is very challenging as the sensor nodes are in a 3D space and are always in passive movement. Thus providing scalable and efficient energy aware routing services and localization schemes has always been provocative. Depth based routing (DBR) is one of the routing protocols that has been in use to attend to the existing constraints of UWSN. Unlike most of the routing protocols that require full dimensional location information of the sensor nodes, DBR needs only the depth information for routing. Also an energy-efficient game theoretic model based on Single-leader-multi-follower Stackelberg game that follows a socially optimal Stackleberg-Nash-Cournot Equilibrium has been in use for topology control of unlocalized and localized sensor nodes that are closed to the surface. A cross layer UWSN architecture for marine environment monitoring is proposed that uses the adaptive neuro fuzzy based interference system to determine the depth of the sensor nodes and the game theoretic model for localization of the sensor nodes at the upper hull of the sea. Using the depth DBR protocol reports the events to the localized sensor nodes that are close to the sea surface which in turn forwards the reported events to the sink. This cross layer UWSN architecture proves to be energy efficient and apt for marine environment monitoring. The architecture is structured and simulated in Aqua-Sim.