E2DTS: An energy efficiency distributed time synchronization algorithm for underwater acoustic mobile sensor networks

Li, Zhengbao; Hong, Feng; Lü, Hong

doi:10.1016/j.adhoc.2011.03.008

Cited by 33 publications

(22 citation statements)

References 15 publications

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“…However, HMR-LEACH algorithm would work more rounds than other algorithms thus increasing the time. Li et al (2013) presented an energy efficiency distributed time synchronisation (E2DTS) algorithm for underwater acoustic node mobility networks, which determined both clock skew and offset. The relationship between time-varying propagation delay and nodes mobility was estimated and then the clock skew.…”

Section: Related Workmentioning

confidence: 99%

Reliable and energy efficient cluster-based architecture for underwater wireless sensor networks

Anuradha

Srivatsa

2018

IJMNDI

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Underwater wireless sensor network (UWSN) provides a promising solution for discovering the aqueous environment efficiently which operates under many important constraints. At one side, these environments are not sufficient in case of energy efficiency and reliability. So in our paper we propose to develop a reliable and energy efficient cluster-based architecture for UWSN. Here the nodes cluster themselves and forms a cluster head. Next by deploying the courier nodes in the network data is aggregated from the CH. They also enable an intercluster communication to forward the sensed data. This increases the lifetime and the delay is less with the reduced buffer overflow problem.

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Section: Related Workmentioning

confidence: 99%

Reliable and energy efficient cluster-based architecture for underwater wireless sensor networks

Anuradha

Srivatsa

2018

IJMNDI

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“…The work presented in [ 13 ] focuses on the time synchronization in underwater acoustic mobile sensor networks (UAMSNs). The work reports the development of an RF-based algorithm, which is bidirectional.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Time Synchronization Support in Wireless Sensor Networks

Bruscato

Heimfarth

Freitas

2017

Sensors

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With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for most of applications, the acquired data must be coherent in terms of the time in which they are acquired, which implies that the entire sensor network presents a certain level of time synchronization. Moreover, to efficiently exchange and forward data, many communication protocols used in WSN rely also on time synchronization among the sensor nodes. Observing the importance in complying with this need for time synchronization, this work focuses on the second synchronization problem, proposing, implementing and testing a time synchronization service for low-power WSN using low frequency real-time clocks in each node. To implement this service, three algorithms based on different strategies are proposed: one based on an auto-correction approach, the second based on a prediction mechanism, while the third uses an analytical correction mechanism. Their goal is the same, i.e., to make the clocks of the sensor nodes converge as quickly as possible and then to keep them most similar as possible. This goal comes along with the requirement to keep low energy consumption. Differently from other works in the literature, the proposal here is independent of any specific protocol, i.e., it may be adapted to be used in different protocols. Moreover, it explores the minimum number of synchronization messages by means of a smart clock update strategy, allowing the trade-off between the desired level of synchronization and the associated energy consumption. Experimental results, which includes data acquired from simulations and testbed deployments, provide evidence of the success in meeting this goal, as well as providing means to compare these three approaches considering the best synchronization results and their costs in terms of energy consumption.

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“…UWSNs localization mainly faces the following difficulties: (1) In UWSNs, the underwater acoustic channel has special characteristics such as narrow bandwidth, high propagation delay, and severe multipath scattering [8][9], which lead to large ranging error and greatly affect the accuracy of the ranging-based localization algorithm. (2) Because the deployment of underwater nodes is large, and the number of beacon nodes is small and the distribution is sparse, the localization algorithm relying on high-density beacon nodes cannot be used.…”

Section: Introductionmentioning

confidence: 99%

A Localization Algorithm for Underwater Wireless Sensor Networks Based on Ranging Correction and Inertial Coordination

Guo¹,

Kang²,

Han³

et al. 2019

KSII TIIS

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Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

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E2DTS: An energy efficiency distributed time synchronization algorithm for underwater acoustic mobile sensor networks

Cited by 33 publications

References 15 publications

Reliable and energy efficient cluster-based architecture for underwater wireless sensor networks

Reliable and energy efficient cluster-based architecture for underwater wireless sensor networks

Enhancing Time Synchronization Support in Wireless Sensor Networks

A Localization Algorithm for Underwater Wireless Sensor Networks Based on Ranging Correction and Inertial Coordination

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