Abstract-Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff between localization accuracy, localization coverage and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.
In oceans, both the natural acoustic systems (such as marine mammals) and artificial acoustic systems [like underwater acoustic networks (UANs) and sonar users] use acoustic signal for communication, echolocation, sensing, and detection. This makes the channel spectrum heavily shared by various underwater acoustic systems. Nevertheless, the precious spectrum resource is still underutilized temporally and spatially in underwater environments. To efficiently utilize the spectrum while avoiding harmful interference with other acoustic systems, a smart UAN should be aware of the surrounding environment and reconfigure their operation parameters. Unfortunately, existing UAN designs have mainly focused on the single network scenario, and very few studies have considered the presence of nearby acoustic activities. In this paper, we advocate cognitive acoustic as a promising technique to develop an environment-friendly UAN with high spectrum utilization. However, underwater cognitive acoustic networks (UCANs) also pose grand challenges due to the unique features of underwater channel and acoustic systems. In this paper, we comprehensively investigate these unique characteristics and their impact on the UCAN design. Finally, possible solutions to tackle such challenges are advocated.
Due to the long propagation delay and high error rate of acoustic channels, it is very challenging to provide reliable data transfer for time-critical applications in an energy-efficient way. On the one hand, traditional retransmission upon failure usually introduces very large end-to-end delay and is thus not proper for time-critical services. On the other hand, common approaches without retransmission consume lots of energy. In this paper, we propose a new multipath power-control transmission (MPT) scheme, which can guarantee certain end-to-end packet error rate while achieving a good balance between the overall energy efficiency and the end-to-end packet delay. MPT smartly combines power control with multipath routing and packet combining at the destination. With carefully designed power-control strategies, MPT consumes much less energy than the conventional one-path transmission scheme without retransmission. Besides, since no hop-by-hop retransmission is allowed, MPT introduces much shorter delays than the traditional one-path scheme with retransmission. We conduct extensive simulations to evaluate the performance of MPT. Our results show that MPT is highly energy-efficient with low end-to-end packet delays.Index Terms-Applications, energy efficiency, network communications, underwater sensor networks.
Time synchronization is a critical service for distributed network systems. In this work, we investigate this problem in the context of underwater sensor networks (UWSNs). Although there are many time synchronization protocols proposed for terrestrial wireless sensor networks, none of them could be directly applied to UWSNs. This is because most of these protocols do not consider long propagation delays and sensor node mobility, which are important characteristics in UWSNs. Further, UWSNs usually have very high requirements in network lifetime and synchronization accuracy. To satisfy these needs, innovative time synchronization solutions are demanded. In this paper, we propose a novel time synchronization scheme, called "Mobi-Sync", for mobile underwater acoustic sensor networks. Mobi-Sync novelly utilizes the spatial correlation of underwater mobile sensor nodes to estimate the long dynamic propagation delays. Simulation results show that Mobi-Sync outperforms existing schemes in both accuracy and energy efficiency.
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