A fully distributed deployment algorithm for underwater strong <i>k</i>-barrier coverage using mobile sensors

Shen, Weiqiang; Zhang, Chuanlin; Zhang, Xiaona; Shi, Jing

doi:10.1177/1550147719838196

Cited by 8 publications

(4 citation statements)

References 41 publications

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“…In [27], the authors propose a Fully Distributed Deployment Algorithm to construct 3D multi-level k-barrier coverage for a UWSN using available sensor nodes. The target is to ensure the security of the network area and detect any intrusion.…”

Section: Free Mobility Deploymentmentioning

confidence: 99%

Self-Adjustment Energy Efficient Redeployment Protocol for Underwater Sensor Networks

Mahfoudh

2023

Sensors

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The diversity of applications supported by Underwater Sensor Networks (UWSNs) explains the success of this type of network and the increasing interest in exploiting and monitoring seas and oceans. One of the most important research fields is network deployment, since this deployment will affect all other research aspects in the UWSNs. Moreover, the initial random deployment resulting from scattering underwater sensor nodes on the network area’s surface does not ensure this area’s coverage and network connectivity. In this research, we propose a self-adjustment redeployment protocol that enhances network coverage and connectivity while reducing the energy consumed during network deployment. This protocol takes into account the peculiar dynamism of the underwater environment due to the water currents. First, we study the impact of these water currents on network deployment. Then, we exploit these water currents to adjust the nodes’ positions to achieve total area coverage and reduce the energy consumed during the deployment by reducing the total distance traveled by the underwater sensor nodes. Simulation results show that the proposed protocol achieves a very high coverage rate (97%) and reduces the distance traveled by nodes during the deployment by 41%.

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Section: Free Mobility Deploymentmentioning

confidence: 99%

Self-Adjustment Energy Efficient Redeployment Protocol for Underwater Sensor Networks

Mahfoudh

2023

Sensors

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“…In the work of Shen et al, 54 an energy efficient underwater weak k-barrier is proposed, in which the moving distance is minimized. The authors further extended their work to strong k-barrier coverage in the work of Shen et al 55 Compared to AUV-based mobile barriers, it is cheaper to build an intrusion detection barrier via stationary sensors. Furthermore, the maintenance costs of these deployment strategies are low, and it is especially feasible for long-term ocean monitoring tasks.…”

Section: Related Workmentioning

confidence: 99%

A software-defined multi-modal wireless sensor network for ocean monitoring

Luo

Wang

et al. 2022

International Journal of Distributed Sensor Networks

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The software-defined networking paradigm enables wireless sensor networks as a programmable and reconfigurable network to improve network management and efficiency. However, several challenges arise when implementing the concept of software-defined networking in maritime wireless sensor networks, as the networks operate in harsh ocean environments, and the dominant underwater acoustic systems are with limited bandwidth and high latency, which render the implementation of software-defined networking central-control difficult. To cope with the problems and meet demand for high-speed data transmission, we propose a radio frequency–acoustic software-defined networking-based multi-modal wireless sensor network which leverages benefits of both radio frequency and acoustic communication systems for ocean monitoring. We first present the software-defined networking-based multi-modal network architecture, and then explore two examples of applications with this architecture: network deployment and coverage for intrusion detection with both grid-based and random deployment scenarios, and a novel underwater testbed design by incorporating radio frequency–acoustic multi-modal techniques to facilitate marine sensor network experiments. Finally, we evaluate the performance of deployment and coverage of software-defined networking-based multi-modal wireless sensor network through simulations with several scenarios to verify the effectiveness of the network.

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“…However, the model only covers 58% of the sensing area. Furthermore, Shen et al 4 developed a fully distributed deployment algorithm to automatically transfer all mobile sensors distributed in underwater space to desired locations, resulting in maximum-level underwater high k-barrier coverage. The proposed algorithm outperforms the Hungarian and HungarianK approaches regarding the length of construction of k-barrier coverage.…”

Section: Related Workmentioning

confidence: 99%

Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks

Fattah

Ahmedy

Idris

et al. 2022

International Journal of Distributed Sensor Networks

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Underwater wireless sensor networks have grown considerably in recent years and now contribute substantially to ocean surveillance applications, marine monitoring and target detection. However, the existing deployment solutions struggle to address the deployment of mobile underwater sensor nodes as a stochastic system. The system faces internal and external environment problems that must be addressed for maximum coverage in the deployment region while minimizing energy consumption. In addition, the existing traditional approaches have limitations of improving simultaneously the objective function of network coverage and the dissipated energy in mobility, sensing and redundant coverage. The proposed solution introduced a hybrid adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition approach by adapting the original non-dominated sorting genetic algorithm II. This study evaluated the solution to substantiate its efficacy, particularly regarding the nodes’ coverage rate, energy consumption and the system’s Pareto optimal metrics and execution time. The results and comparative analysis indicate that the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy) is a better solution to the multi-objective sensor node deployment problem, outperforming the non-dominated sorting genetic algorithm II, SPEA2 and MOEA/D algorithms. Moreover, MOGA-AMPazy ensures maximum global convergence and has less computational complexity. Ultimately, the proposed solution enables the decision-maker or mission planners to monitor effectively the region of interest.

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A fully distributed deployment algorithm for underwater strong k-barrier coverage using mobile sensors

Cited by 8 publications

References 41 publications

Self-Adjustment Energy Efficient Redeployment Protocol for Underwater Sensor Networks

Self-Adjustment Energy Efficient Redeployment Protocol for Underwater Sensor Networks

A software-defined multi-modal wireless sensor network for ocean monitoring

Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks

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