Research on Sensor Network Coverage Enhancement Based on Non-cooperative Games

Duan, Chaofan; Feng, Jing; Chang, Haotian; Pan, Jianping; Duan, Liming

doi:10.32604/cmc.2019.06033

Cited by 16 publications

(11 citation statements)

References 9 publications

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“…However, the authors of [18] did not consider cluttered environments or mobile sensor nodes, which are considered in our paper. Considering mobile sensor nodes, [19] addressed a non‐cooperative game model for the sensor network deployment and a local information‐based topology control for coverage enhancement. But, [19] did not consider cluttered environments or complete coverage without sensing holes, which are considered in our paper.…”

Section: Introductionmentioning

confidence: 99%

Coverage control of multiple robots in cluttered three‐dimensional environments

Kim

2021

IET Radar Sonar & Navi

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Distributed network systems can be utilized to measure environmental conditions such as temperature, sound, pollution levels, humidity, wind, and so on. Multiple autonomously moving mobile sensors are used to construct distributed sensor networks in an unknown cluttered 3-D workspace. The proposed strategy is to deploy mobile sensors (robots) sequentially and individually to extend the network until the network fully covers the entire open space. This strategy results in 3-D sensor networks without sensing holes and does not require global localization of a robot except for a single robot called the Communication Navigation Aid. The authors believe this article is unique in constructing sensor networks in 3-D workspaces cluttered with many obstacles. Moreover, this article presents an innovative recovery algorithm to handle sensor failures in the constructed network. Network connectivity is maintained while robots move in unknown 3-D cluttered environments. Once a robot is deployed at its designated location, it becomes localized in global coordinate systems. Utilizing MATLAB, the effectiveness of the proposed deployment methods is demonstrated.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Coverage control of multiple robots in cluttered three‐dimensional environments

Kim

2021

IET Radar Sonar & Navi

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“…However, it is impossible to perform detailed searches in real-time in HDWSNs [23,24]. erefore, numerous heuristic algorithms have been created to reduce WSNs communication power consumption and improve WSNs performance [25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Clone Chaotic Parallel Evolutionary Algorithm for Low-Energy Clustering in High-Density Wireless Sensor Networks

Yang

Zhou

2021

Scientific Programming

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Because the sensors are constrained in energy capabilities, low-energy clustering has become a challenging problem in high-density wireless sensor networks (HDWSNs). Usually, sensor nodes tend to be tiny devices along with constrained clustering abilities. To have a low communication energy consumption, a low-energy clustering scheme should be designed properly. In this work, a new cloned chaotic parallel evolution algorithm (CCPEA) is proposed, and a low-energy clustering model is established to lower the communication energy consumption of HDWSNs. By introducing CCPEA into the low-energy clustering, an objective function is designed for evaluating the communication energy consumption. For this problem, we define a clone operator to minimize the communication energy consumption of HDWSNs, use the chaotic operator to randomly generate the initial population to expand the search range to avoid local optimization, and find the parallel operator to speed up the convergence speed. In the experiment, the effect of CCPEA is compared to heuristic approaches of particle swarm optimization (PSO) and simulated annealing (SA) for the HDWSNs with different numbers of sensors. Simulation experiments demonstrate that the presented CCPEA method achieves a lower communication energy consumption and faster convergence speed than PSO and SA.

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“…The redeployment was used in adding new nodes to the network to replace some broken. A postdeployment phase is used when the network topology has been evolved due to a relocation of nodes [15,16]. According to the density, a sensor network deployment could be a sparse or dense deployment in which low or high number of sensors is used to cover AoI, respectively.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm

et al. 2020

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Due to the increase of Wireless Sensor Network (WSN) technologies demand, the optimal sensor node deployment is considered as one of the most important factors that directly affect the network coverage. Most researches in WSNs that solved the problem of coverage in homogeneous and heterogeneous cases are suffering from many drawbacks such as consumed energy and high cost. In this paper, we propose an efficient deployment model based on probabilistic sensing model (PSM) and harmony search algorithm (HSA) to achieve the balance between the network coverage performance and the network cost in a heterogeneous wireless sensor network (HEWSN). The HSA is used for deployment optimization of HEWSN nodes which makes a balance between the coverage and financial cost. The PSM is used to solve the overlapping problem among the sensors. The performance of the proposed model is analyzed in terms of coverage ratio and cost evaluations. The simulation results showed the capability of the proposed heterogeneous deployment model to achieve maximum coverage and a minimum number of sensors compared to homogeneous deployment. Furthermore, a comparative study with a meta-heuristic genetic-based algorithm in HEWSN has also been conducted, and its results confirm the superiority of the proposed model.

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Research on Sensor Network Coverage Enhancement Based on Non-cooperative Games

Cited by 16 publications

References 9 publications

Coverage control of multiple robots in cluttered three‐dimensional environments

Coverage control of multiple robots in cluttered three‐dimensional environments

Clone Chaotic Parallel Evolutionary Algorithm for Low-Energy Clustering in High-Density Wireless Sensor Networks

An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm

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