Energy-Efficient Depth Based Probabilistic Routing Within 2-Hop Neighborhood for Underwater Sensor Networks
Meiyan Zhang, Wenyu Cai
Abstract
Underwater sensor networks (UWSNs) have recently been regarded as a promising method to monitor and explore underwater environments. Reliable and efficient data transmission to Sink is one of most important concerns of UWSNs. In this letter, we propose an energy-efficient probabilistic depth-based routing (EEPDBR) for UWSNs, which is improved from traditional depth-based routing (DBR) algorithm. The key idea of EEPDBR algorithm is to design an improved probabilistic DBR algorithm for reliable underwater data reporting to any surface sonobuoy, which takes node's depth, residual energy, and forwarding number within its 2-hop neighborhood into account. Extensive simulation results verify that the proposed EEPDBR method can achieve higher packet delivery ratio and lower average delivery time, while saving energy consumption effectively comparing to existing methods.