Cellular automaton based algorithms for depth adjustment in underwater mobile sensor networks

Three dimensional wireless sensor networks have been extensively studied due, in part, to their applications in underwater sensing. Often algorithmic solutions to analogous problems in two and three dimensions, respectively, can be significantly different. Though there have been many algorithms proposed for two dimensional sensor movement problems, there are very few in the case of three dimensional networks. In this paper we propose cellular automaton based probabilistic depth adjustment algorithms for sensors in underwater networks. Sensors are initially deployed close to the surface and our main goal is to disperse them vertically to maximize the coverage of the network while maintaining the connectivity. We compare our proposed algorithms for three different pairs of communication (R_c) and sensing (R_s) radii. We find that for R_c = 3 and R_s = 1, our algorithm finds the optimal solution. For the other two pairs the algorithm finds solutions that are reasonably close to the used benchmark solutions.