Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

Jiang, Peng; Yang, Feng; Wu, Feng

doi:10.3390/s16101754

Cited by 16 publications

(7 citation statements)

References 24 publications

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“…Under the condition of ensuring certain service quality (QOS), the network node should be used as few as possible to achieve maximum network coverage scope. In the optimization of network coverage [8][9][10][11][12] for mobile sensor networks, we need to consider both node coverage and regional coverage.…”

Section: Problem Descriptionmentioning

confidence: 99%

[Retracted] Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space

Gao

Lyu

et al. 2021

Wireless Communications and Mobile Computing

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Mobile sensor network is applied in information collection in emergencies. As the mobile sensor network in real environment is widely deployed with different height and the redundancy of the sensor node needs to be as low as possible, therefore, it is necessary to effectively deploy mobile sensor nodes in the 3D space to have reasonable layout and optimized density. To this end, we established the optimization model of mobile sensor network deployment and solved the model with chemical reaction optimization (CRO). The experimental results have shown that compared with traditional particle swarm optimization (PSO), CRO algorithm can achieve reasonable deployment more rapidly and enhance the network performance evaluation value effectively. The reasonable deployment of mobile sensor network node is very significant to information collecting, postperiod decision-making, and rapid rescuing work in emergencies.

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Section: Problem Descriptionmentioning

confidence: 99%

[Retracted] Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space

Gao

Lyu

et al. 2021

Wireless Communications and Mobile Computing

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“…An underwater mobile node deployment algorithm based on wolf colony search was proposed. 38 According to the underwater environment with obstacles, the algorithm combined wolf colony search with the degree of crowding to avoid falling into the local optimum under the premise of ensuring the coverage of target events. Compared with the artificial fish swarm algorithm, 33 the algorithm showed the high coverage, low energy consumption, and obstacle avoidance.…”

Section: Configuration Mechanismsmentioning

confidence: 99%

Topological configuration and optimization in underwater acoustic sensor networks: A survey

Chen

Dai

et al. 2018

International Journal of Distributed Sensor Networks

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Marine environmental monitoring, marine resource development, and maritime rights and interests protection had put great demands on underwater acoustic sensor networks. At the same time, it was found that the configuration and optimization of the underwater acoustic sensor network had important influence on the network performance and service quality in the uncertain marine environment. According to the characteristics of dynamic evolution of network topology and combining with different practical application scenarios, this article studied and discussed the model description, configuration mechanism, and optimization strategy of underwater acoustic sensor network. First, the classical underwater acoustic sensor network models were divided and discussed from three aspects: dimension, sensor types, and dynamic and static states. The characteristics of the six models are compared and analyzed. Second, according to the characteristics of six different models, the configuration mechanism and optimization strategy are discussed and classified. The configuration mechanism of models was studied from the aspects about determinism, self-adaptation, and group intelligence. The optimization strategy of models was discussed from the aspects about coverage, connectivity, energy consumption, time delay, data quality, and so on, and the relations and differences between different methods were compared and analyzed. Finally, the five future researches direction were expected, in order to provide a clear idea for further research in this field.

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“…The monitoring area is regarded as a thin sea surface in underwater space. Similar to [ 31 ], the monitoring area can be divided into multiple equally-sized virtual lattices. Then, a set of SNs is randomly deployed in the sea surface.…”

Section: Algorithm Description and Analysismentioning

confidence: 99%

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

Yan

Luo

et al. 2017

Sensors

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Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods.

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Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

Cited by 16 publications

References 24 publications

[Retracted] Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space

[Retracted] Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space

Topological configuration and optimization in underwater acoustic sensor networks: A survey

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

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