Enhanced Deployment Algorithms for Heterogeneous Directional Mobile Sensors in a Bounded Monitoring Area

Lin, Ting-Yu; Santoso, Hendro Agus; Wu, Kun-Feng; Wang, Gui-Liu

doi:10.1109/tmc.2016.2563435

Cited by 41 publications

(21 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To better consider the coverage problem, we propose a 3D directional sensing model by simultaneously considering the sensing distance and horizontal and vertical sensing angles, which is probabilistic to improve precision and practicability. Also, our model has considered supporting heterogeneous directional sensor nodes [21] with improved practicability. In this paper, we inspired from the idea of particle swarm optimisation [22] and simultaneously deploy sensor nodes and relay nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

3-D Multiobjective Deployment of an Industrial Wireless Sensor Network for Maritime Applications Utilizing a Distributed Parallel Algorithm

Cao

Zhao

Yang

et al. 2018

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

Abstract-Effective monitoring marine environment has become a vital problem in the marine applications. Traditionally, marine application mostly utilizes oceanographic research vessel methods to monitor the environment and human parameters. But these methods are usually expensive and time-consuming, also limited resolution in time and space. Due to easy deployment and cost-effective, WSNs have recently been considered as a promising alternative for next generation IMGs. This paper focuses on solving the issue of 3D WSN deployment in a 3D engine room space of a very large crude-oil carrier (VLCC), in which many power devices are also considered. To address this 3D WSN deployment problem for maritime applications, a 3D uncertain coverage model is proposed with a new 3D sensing model and an uncertain fusion operator, is presented. The deployment problem is converted into a multi-objective problems (MOP) in which three objectives are simultaneously considered: Coverage, Lifetime and Reliability. Our aim is to achieve extensive Coverage, long Lifetime and high Reliability. We also propose a distributed parallel cooperative co-evolutionary multi-objective large-scale evolutionary algorithm (DPCCMOLSEA) for maritime applications. In the simulation experiments, the effectiveness of this algorithm is verified in comparing with five state-of-the-art algorithms. The numerical outputs demonstrate that the proposed method performs the best with respect to both optimization performance and computation time.Index Terms-wireless sensor network deployment, 3D engine room, Very large crude-oil carrier (VLCC), Coverage, Lifetime, Reliability, Parallel, Multi-objective evolutionary algorithm.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…Based on the work of [21], we transform the reliability constraint into an objective that can be optimized. Assuming that each sensor or relay node is connected to relia R N relay nodes, the fitness of the Reliability objective is as follows: …”

Section: Reliabilitymentioning

confidence: 99%

3-D Multiobjective Deployment of an Industrial Wireless Sensor Network for Maritime Applications Utilizing a Distributed Parallel Algorithm

Cao

Zhao

Yang

et al. 2018

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

show abstract

“…The main idea of their work is to adjust working direction based on resultant force of sensor. Lin et al [14] proposed two enhanced deployment algorithms, EDA-I and EDA-II, respectively. EDA-I adopts the concept of virtual force to instruct the sensor to move or rotate, and EDA-II constructs the Voronoi diagram by the centroid of the sensor’s fan.…”

Section: Related Workmentioning

confidence: 99%

“…We compare RWD, MIC and RB with random deployment, DVSA deployment in [8] and EDA-II deployment in [14] because DVSA and EDA-II both employ the movement and rotation characteristics. In addition, we analyze the impact of the sensing radius and AoV on network coverage ratio.…”

Section: Performance Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

Local Coverage Optimization Strategy Based on Voronoi for Directional Sensor Networks

Zhang

You

Ren

et al. 2016

Sensors

View full text Add to dashboard Cite

In this paper, we study the area coverage of directional sensor networks (DSNs) with random node distribution. The coverage of DSNs depends on the sensor’s locations, the sensing radiuses, and the working directions, as well as the angle of view (AoV), which is challenging to analyze. We transform the network area coverage problem into cell coverage problems by exploiting the Voronoi diagram, which only needs to optimize local coverage for each cell in a decentralized way. To address the cell coverage problem, we propose three local coverage optimization algorithms to improve the cell coverage, namely Move Inside Cell Algorithm (MIC), Rotate Working Direction Algorithm (RWD) and Rotation based on boundary (RB), respectively. Extensive simulations are performed to prove the effectiveness of our proposed algorithms in terms of the coverage ratio.

show abstract

Coverage Optimization using Nature-Inspired Algorithm for Directional Sensor Networks

Ahmad

Shivalingagowda

Kohli

et al. 2021

Springer Tracts in Nature-Inspired Computing

View full text Add to dashboard Cite

Enhanced Deployment Algorithms for Heterogeneous Directional Mobile Sensors in a Bounded Monitoring Area

Cited by 41 publications

References 25 publications

3-D Multiobjective Deployment of an Industrial Wireless Sensor Network for Maritime Applications Utilizing a Distributed Parallel Algorithm

3-D Multiobjective Deployment of an Industrial Wireless Sensor Network for Maritime Applications Utilizing a Distributed Parallel Algorithm

Local Coverage Optimization Strategy Based on Voronoi for Directional Sensor Networks

Coverage Optimization using Nature-Inspired Algorithm for Directional Sensor Networks

Contact Info

Product

Resources

About