Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory

Xia, Na; Ou, Yuanxiao; Wang, Shiliang; Zheng, Rong; Du, Huazheng; Xu, Chaonong

doi:10.1109/tmc.2016.2586051

Cited by 19 publications

(6 citation statements)

References 40 publications

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“…The UWSN node localization problem is a subset of the MUWSN localization. Nevertheless, even the problem of UWSN localization is significantly difficult, as has been illustrated in previous studies [2,6,7]. There are much more issues to be explored in MUWSN localization.…”

Section: Introductionmentioning

confidence: 95%

“…The drifting is caused by the interaction of different ocean currents and tides or internal waves [23,24,25]. Xia et al [6] proposed a skeleton scheme that adopted the global rigidity to determine the set of localizable sensor nodes. With this localizable node set, an Analytic Hierarchy Process (AHP) evaluates the localization confidence of the sensor nodes.…”

Section: Preliminaries and Related Workmentioning

confidence: 99%

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ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks

Zhou

et al. 2019

Sensors

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We study the problem of three-dimensional localization of the underwater mobile sensor networks using only range measurements without GPS devices. This problem is challenging because sensor nodes often drift with unknown water currents. Consequently, the moving direction and speed of a sensor node cannot be predicted. Moreover, the motion devices of the sensor nodes are not accurate in underwater environments. Therefore, we propose an adaptive localization scheme, ProLo, taking these uncertainties into consideration. This scheme applies the rigidity theory and maintains a virtual rigid structure through projection. We have proved the correctness of this three-dimensional localization scheme and also validated it using simulation. The results demonstrate that ProLo is promising for real mobile underwater sensor networks with various noises and errors.

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Section: Introductionmentioning

confidence: 95%

Section: Preliminaries and Related Workmentioning

confidence: 99%

ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks

Zhou

et al. 2019

Sensors

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“…Assuming that o represents the target position, s j denotes the repair node, and each virtual force is expressed as represents Euclidean distance between the two sensor nodes; Q represents disturbance amplitude of random disturbance force. The resultant force acted by the repair node is expressed by equation (18). When the resultant force is 0 or in the opposite direction of the last resultant force, the node does not move.…”

Section: The Edge Node Processes the Take Messagementioning

confidence: 99%

“…The resultant force acted by the repair node is expressed by equation (18). When the resultant force is 0 or in the opposite direction of the last resultant force, the node does not move.…”

Section: The Edge Node Processes the Take Messagementioning

confidence: 99%

“…1,[25][26][27][28][29][30] The quality of communication among the sensor nodes and the reliability of topology of UASNs have been seriously affected due to 1 the factors of complex marine environment, such as the high latency, low bandwidth, and easy attenuation of signal and multipath effects, seriously affecting. [15][16][17][18][19][20][21][22][23] Currently, optimization for terrestrial sensor networks has some achievements. Fu and Han 2 solve the sensor node-distributed optimization problems of the terrestrial sensor network by quantum genetic algorithm; Aziz et al 3 consider comprehensively the battery power of sensor and other factors, then employing the distributed topology control technology to optimize the energy consumption of wireless sensor networks; Wang et al 4 present a parallel particle swarm optimization (PSO) strategies based on the mobility of sensor node, so that distribution of the node in sensor networks reaches local optimum; Mi and Zhou 5 proposed a terrestrial wireless sensor network routing algorithm multi-objective optimization.…”

Section: Introductionmentioning

confidence: 99%

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A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles

Liu

Zhang

et al. 2017

International Journal of Distributed Sensor Networks

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Limited energy, high mobility, and unsteady acoustic communication links render the underwater acoustic sensor networks subject to performance reduction. To solve this problem, a topology optimization method, also called TO-A algorithm, is developed based on topology reconfiguration. First, the proposed method optimizes the coverage rate of underwater acoustic sensor networks by adjusting the location of sensor nodes through simulating fish behaviors. Second, to optimize the connectivity of underwater acoustic sensor networks, the proposed method, using edge nodes, repairs disconnected positions and eliminates key nodes in underwater acoustic sensor networks. Third, a topology optimization strategy, also called TO-DA algorithm, is developed for Double-autonomous underwater vehicles to improve the robustness and adaptability of the network topology. When the inherent law of underwater acoustic sensor networks topology formation is further found, the method for optimizing network topology is proposed, which based on the triangle principle eliminates those key nodes and can help with the survivability of network regeneration. The method proves reasonable and valid by stimulation and contrast examinations. The comparison of TO-A algorithm and TO-DA algorithm shows that under low energy consumption, TO-A algorithm can keep the network coverage at about 97% for a long time, connectivity rate above 89%, while the TO-DA algorithm can improve the survivability of the network by above 50% at the expense of 8.5% of the network coverage.

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A survey on node localization technologies in UWSNs: Potential solutions, recent advancements, and future directions

Nain,

Goyal,

Dhurandher

et al. 2024

Int J Communication

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SummaryLocation‐based underwater communication applications such as strategic surveillance, disaster prevention, marine research, and mine detection have given the field of underwater wireless sensor networks (UWSN) a head start. Node localization is a prerequisite for accurate data collection, target monitoring, and network management in UWSNs. However, the unique characteristics of the underwater environment, such as signal attenuation, multipath propagation, and variable acoustic properties, pose a major challenge to effective node localization. Accurate sensor node location data is essential for successful underwater data collection, but difficult to achieve as the GPS system cannot be used in an underwater environment. In this paper, existing node localization techniques such as ALS, SLUM, MASL, SLMP, UDB, USP, etc., and recent advances such as the fusion of range‐based and range‐free techniques, the fusion of RSSI and AoA to improve localization accuracy by using directional information in addition to signal strength, and the use of optimization techniques such as PSO, COA, and WOA algorithms to improve the accuracy of the applied node localization algorithm, e.g., TP‐TSFLA, and challenges related to UWSN are discussed. Also, different localization algorithms that affect the accuracy of UWSN localization techniques have been evaluated and compared with NS2 in terms of localization error, localization coverage, energy consumption, and average communication cost metrics. In addition, this paper also provides an up‐to‐date investigation of localization techniques. Finally, the tools available for simulation are presented, followed by open research questions that need to be addressed in the localization of nodes.

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Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory

Cited by 19 publications

References 40 publications

ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks

ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks

A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles

A survey on node localization technologies in UWSNs: Potential solutions, recent advancements, and future directions

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