Underwater Wireless Sensor Networks: How Do Acoustic Propagation Models Impact the Performance of Higher-Level Protocols?

Abstract

Several Medium Access Control (MAC) and routing protocols have been developed in the last years for Underwater Wireless Sensor Networks (UWSNs). One of the main difficulties to compare and validate the performance of different proposals is the lack of a common standard to model the acoustic propagation in the underwater environment. In this paper we analyze the evolution of underwater acoustic prediction models from a simple approach to more detailed and accurate models. Then, different high layer network protocols are tested with different acoustic propagation models in order to determine the influence of environmental parameters on the obtained results. After several experiments, we can conclude that higher-level protocols are sensitive to both: (a) physical layer parameters related to the network scenario and (b) the acoustic propagation model. Conditions like ocean surface activity, scenario location, bathymetry or floor sediment composition, may change the signal propagation behavior. So, when designing network architectures for UWSNs, the role of the physical layer should be seriously taken into account in order to assert that the obtained simulation results will be close to the ones obtained in real network scenarios.

Effect of near-surface bubble plumes on the acoustic signal used in UWACNs

“…The average velocity of an acoustic signal in ocean is 1500 m/s [8]. Therefore, in such medium, a high frequency acoustic source will have a few meters of wavelength.…”

“…In this equation, γ is the ratio of specific heats having value as 1.4, r 0 is the bubble plume radius, which is considered to be 60 μm, φ = Ω 2D , D is the thermal diffusivity with value 1.84×10 −5 m 2 /s, and ρ = 1025 kg/m 3 , is the average density of ocean water. Considering all the above parameters, Equation (8), in the absence of any acoustic source can be expressed as:…”

SEDG: Scalable and Efficient Data Gathering Routing Protocol for Underwater WSNs

“…Delay can be computed by using end-to-end delay model 14 . The propagation delay T P is the main component of this model.…”

A new algorithm based on discrete fourier transform to improve the lifetime of underwater Wireless Sensor Networks communications

“…It can either reduce or increase the power consumption. Hence, if these parameters are not set to the optimal values, the transmitted signal will be lost due to the ionized nature of sea water [15]. Table 1 shows the initial values that can be adjusted using the implemented simulator.…”

“…al. [15] presents the various parameters used for underwater communication. The paper discusses the transmission distance and frequency.…”