SLSMP: Time Synchronization and Localization Using Seawater Movement Pattern in Underwater Wireless Networks

Kim, Sungryul; Yoo, Younghwan

doi:10.1155/2014/172043

Cited by 10 publications

(10 citation statements)

References 27 publications

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“…We still first consider the active messaging properties based on the stationary state and collect several papers to describe it. In [ 55 ], the time synchronization and localization based on the semi-periodic property of seawater movement scheme is called SLSMP. The deployment is described as follows: the reference nodes attached to the buoys and the sensor nodes equipped with tiny gyro and acceleration sensors are used.…”

Section: Localization Algorithmmentioning

confidence: 99%

Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks

Luo

Fan

et al. 2018

Sensors

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The water source, as a significant body of the earth, with a high value, serves as a hot topic to study Underwater Sensor Networks (UWSNs). Various applications can be realized based on UWSNs. Our paper mainly concentrates on the localization algorithms based on the acoustic communication for UWSNs. An in-depth survey of localization algorithms is provided for UWSNs. We first introduce the acoustic communication, network architecture, and routing technique in UWSNs. The localization algorithms are classified into five aspects, namely, computation algorithm, spatial coverage, range measurement, the state of the nodes and communication between nodes that are different from all other survey papers. Moreover, we collect a lot of pioneering papers, and a comprehensive comparison is made. In addition, some challenges and open issues are raised in our paper.

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Section: Localization Algorithmmentioning

confidence: 99%

Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks

Luo

Fan

et al. 2018

Sensors

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“…Its accuracy is vulnerable to multiple factors such as time synchronization, multipath effect and stratification effect. In SLSMP [ 14 ] and STSL [ 15 ], time synchronization is first performed to get clock skew and offset between beacon nodes and target nodes. Hence, the distance between two synchronized nodes can be estimated precisely.…”

Section: Related Workmentioning

confidence: 99%

STVF: Spatial-Temporal Variational Filtering for Localization in Underwater Acoustic Sensor Networks

Sun

Luo

et al. 2018

Sensors

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Localization is one of the critical services in Underwater Acoustic Sensor Networks (UASNs). Due to harsh underwater environments, the nodes often move with currents continuously. Consequently, the acoustic signals usually propagate with varying speeds in non-straight lines and the noise levels change frequently with the motion of the nodes. These limitations pose huge challenges for localization in UASNs. In this paper, we propose a novel localization method based on a variational filtering technique, in which the spatial correlation and temporal dependency information are utilized to improve localization performance. In the method, a state evolution model is employed to characterize the mobility pattern of the nodes and capture the uncertainty of the location transition. Then, a measurement model is used to reflect the relation between the measurements and the locations considering the dynamics of the acoustic speed and range noise. After that, a variational filtering scheme is adopted to determine the nodes’ locations, which consists of two phases: variational prediction and update. In the former phase, the coarse estimation of each node’ location is computed based on its previous location; in the latter phase, the coarse location is optimized by incorporating the measurements from the reference nodes as precisely as possible. At last, an iterative localization scheme is applied, in which a node labels itself as a reference node if the confidence of its location estimation is higher than the predefined threshold. We conducted extensive simulations under different parameter settings, and the results indicate that the proposed method has better localization accuracy compared to a typical SLMP algorithm while maintaining relatively high localization coverage. Moreover, spatial–temporal variational filtering (STVF) is more robust to the change of the parameter settings compared to SLMP.

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“…The study has even used an iterative Kalman filter. Kim and Yoo [10] have presented a scheme of time synchronization in sensor network considering the challenges of reducing errors occurring undersea bed. The controlling strategy of synchronization is developed by using mobility factor and node usage.…”

Section: Related Workmentioning

confidence: 99%

OTSA: Optimized Time Synchronization Approach for Delay-based Energy Efficient Routing in WSN

Nagarathna¹,

Mallapur²

2017

ijacsa

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Abstract-Time Synchronization is one of the problems and still ignored problem in area of wireless sensor network (WSN). After reviewing the existing literatures, it is found that there are few studies that combinely address the problem of energy conservation, clustering, routing along with minimizing the errors due to time synchronization in sensor network. Therefore, this manuscript presents a delay-based routing which considers the propagation delay to formulate a mechanism for delay compensation in large scale wireless sensor network. The prime goal of this technique is to jointly address energy problems, time synchronization, and routing in wireless sensor network. The outcome of the proposed study was found to posse's minimized communication overhead, minimized synchronization errors, lower energy consumption, and reduced processing time when compared with the existing standards of time synchronization techniques.

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SLSMP: Time Synchronization and Localization Using Seawater Movement Pattern in Underwater Wireless Networks

Cited by 10 publications

References 27 publications

Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks

Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks

STVF: Spatial-Temporal Variational Filtering for Localization in Underwater Acoustic Sensor Networks

OTSA: Optimized Time Synchronization Approach for Delay-based Energy Efficient Routing in WSN

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