Enhanced Dwarf Mongoose Optimization Based Node Localization Scheme for Underwater Wireless Sensor Networks

Recently, the Underwater Wireless Sensor Network (UWSN) with movable nodes has been launched because it has a lot of potential uses in aquatic science and is getting a lot of attention from researchers. Because there are so many more possible underwater uses, it is important to make sure that signals can get from one underwater point to another. Because of the long lags in signal transmission and the changing speed of sound underwater, it is hard and not possible to use the usual localization method in UWSN. Node localization (NL) in UWSN tries to figure out where new nodes are by using known nodes. The correctness of location can have a big effect on how well a UWSN works. UWSN has a lot of trouble with precise NL. When it comes to WSN, NL problems mean figuring out where unknown sensor nodes (SNs) are. This shows how important it is to have a perfect NL system. The Enhanced Dwarf Mongoose Optimization based Node Localization Scheme (EDMO-NLS) for UWSN is being worked on in this study. The scout group, the alpha group, and the babysitters are the three social groups of dwarf mongooses that were used in the suggested method. The family hunts as a unit, and the main female starts hunting. This sets the sleeping mounds, the road for hunting, and the distance that is covered. The EDMO-NLS method shown here finds nodes whose locations are unknown in UWSN. The modeling results showed that the proposed model worked better than existing methods. Based on the findings and the discussion, it is clear that the suggested method has shown the best localization success in UWSN.