MU-Sync

Chirdchoo, Nitthita; Soh, Wee-Seng; Chua, Kee Chaing

doi:10.1145/1410107.1410115

Cited by 106 publications

(7 citation statements)

References 15 publications

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“…At present, a few time synchronization protocols for underwater sensor networks have been proposed, such as the time synchronization for high latency acoustic networks (TSHL) [25], the time synchronization protocol for underwater mobile networks (MU-Sync) [26], the efficient time synchronization for mobile underwater sensor networks (Mobi-Sync) [27], the Doppler-based time synchronization for mobile underwater sensor networks (D-Sync) [28], and the time synchronization scheme for mobile underwater sensor networks (TSMU) [29]. However, these protocols have their own application scenarios and they all make different assumptions.…”

Section: Related Workmentioning

confidence: 99%

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DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks

Zhou

Wang

Nie

et al. 2018

Sensors

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Time synchronization is the foundation of cooperative work among nodes of underwater sensor networks; it takes a critical role in the research and application of underwater sensor networks. Although numerous time synchronization protocols have been proposed for terrestrial wireless sensor networks, they cannot be directly applied to underwater sensor networks. This is because most of them typically assume that the propagation delay among sensor nodes is negligible, which is not the case in underwater sensor networks. Time synchronization is mainly affected by a long propagation delay among sensor nodes due to the low propagation speed of acoustic signals. Furthermore, sensor nodes in underwater tend to experience some degree of mobility due to wind or ocean current, or some other nodes are on self-propelled vehicles, such as autonomous underwater vehicles (AUVs). In this paper, we propose a Doppler-enhanced time synchronization scheme for mobile underwater sensor networks, called DE-Sync. Our new scheme considers the effect of the clock skew during the process of estimating the Doppler scale factor and directly substitutes the Doppler scale factor into linear regression to achieve the estimation of the clock skew and offset. Simulation results show that DE-Sync outperforms existing time synchronization protocols in both accuracy and energy efficiency.

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Section: Related Workmentioning

confidence: 99%

“…According to the references [25,26,27,28,32], the inherent skew can be selected with the range from 50 to 10 6 ppm. However, the inherent skew rarely can reach 10 6 ppm in practice.…”

Section: Performance Evaluationmentioning

confidence: 99%

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks

Zhou

Wang

Nie

et al. 2018

Sensors

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“…However, distance estimation requires round trip message exchange or prior time synchronization with the beacons. On the other hand, time-sync protocols that take vehicle motion into account, such as MU-Sync [18], D-Sync [19] and Mobi-Sync [20] require bi-directional acoustic signaling with beacons. Therefore, the signaling overhead associated with performing time-sync and tracking independently is substantial.…”

Section: Related Workmentioning

confidence: 99%

ToA-TS: Time of arrival based joint time synchronization and tracking for mobile underwater systems

Mirza

Kastner

et al. 2015

Ad Hoc Networks

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Time synchronization and localization are key requirements for distributed underwater systems consisting of numerous low-cost submersibles. In these systems, submersibles are highly resource constrained and typically have limited acoustic communication capability. We investigate the problem of tracking submersibles that only have the capability of receiving acoustic signals. Traditional Long Base Line (LBL) systems track the location of submersibles by providing a GPS-like infrastructure that consists of a few reference beacons at known locations. In these systems the unknown positions of submersibles are estimated from beacon transmissions using time-di↵erence-of-arrival (TDoA) based localization. As such TDoA makes the key assumption that beacon transmissions occur nearly concurrently in time. While this assumption is ensured in small LBL deployments it does not hold as the size of the system scales up. In this paper we identify scenarios where signals from multiple beacons are significantly lagged in time. We further identify the motion of the submersible between signal arrivals as a key factor that deteriorates the performance of TDoA, when transmissions are not concurrent. To address this problem we propose to track the submersible while performing time-synchronization. Our proposed technique,

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“…But it is impractical that they assumed that all nodes are stationary in the underwater environment. To overcome this limitation, MU-Sync provides time synchronization considering mobile scenario [4]. MU-Sync conducts two phase synchronizations.…”

Section: Related Workmentioning

confidence: 99%

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

Kim

Yoo

2014

International Journal of Distributed Sensor Networks

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Time synchronization and localization in underwater environment are challenging due to high propagation delay, time measurement error, and node mobility. Although synchronization and localization depend on each other and have the similar process, they have been usually handled separately. In this paper, we suggest time synchronization and localization based on the semiperiodic property of seawater movement, called SLSMP. Firstly, we analyze error factors in time synchronization and localization and then propose a method to handle those errors. For more accurate synchronization, SLSMP controls the transmission instant by exploiting the pattern of seawater movement and node deployment. Then SLSMP progressively decreases the localization errors by applying the Kalman filter or averaging filter. Finally, INS (inertial navigation system) is adopted to relieve localization error caused by node mobility and error propagation problem. The simulation results show that SLSMP reduces time synchronization error by 2.5 ms and 0.56 ms compared with TSHL and MU-Sync, respectively. Also localization error is lessened by 44.73% compared with the single multilateration.

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MU-Sync

Cited by 106 publications

References 15 publications

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks

ToA-TS: Time of arrival based joint time synchronization and tracking for mobile underwater systems

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

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