This paper focuses on studying the sensor nodes deployment towards accurate data fusion for ship movement controlling. Furthermore, this study provides a node deployment layout with better measurement accuracy, which ...
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ISBN:
(纸本)9781450319591
This paper focuses on studying the sensor nodes deployment towards accurate data fusion for ship movement controlling. Furthermore, this study provides a node deployment layout with better measurement accuracy, which is surprisedly different from the layout that we originally predicted.
Wireless sensor networks contribute to significantly reduce energy, consumption in green buildings. The sensor node deployment is a crucial problem in WSNs. This paper formulates the deployment model of sensornodes f...
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ISBN:
(纸本)9781479917174
Wireless sensor networks contribute to significantly reduce energy, consumption in green buildings. The sensor node deployment is a crucial problem in WSNs. This paper formulates the deployment model of sensornodes for target detection and location in a horizontal plane of a building and introduces an objective function with two constraints for the optimization problem. The problem is transformed into an unconstraint function by using penalty functions. The function acts as the fitness function in the improved adaptive binary particle swarm optimization algorithm. The simulation results show that the algorithm achieves the required target detection and location accuracy under the full coverage and a limited budget. Furthermore, the convergence rate and solution are better than the standard binary particle swarm optimization algorithm.
The wireless sensor network (WSN) coverage is one of the most significant impacts on the quality of service that directly determines the efficiency reality of applications. The distribution of sensornodes in the WSN ...
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The wireless sensor network (WSN) coverage is one of the most significant impacts on the quality of service that directly determines the efficiency reality of applications. The distribution of sensornodes in the WSN determines the size of the network monitoring coverage area, whether there is duplicate coverage, and monitoring blind regions. This study introduces an optimal coverage strategy for the sensor node positions in the sensing region based on an adapted transit search (ATS) algorithm. The transit search (TS) algorithm is a recently developed metaheuristic algorithm with several advantages, e.g. simple concept, robust process, and ease of implementation;still, TS has limitations in the ratios of exploration and exploitation for avoiding the local optimum trap when dealing with complicated node coverage optimization situations. The ATS is implemented by adapting and updating equations with stochastic reverse learning and multi-direction strategies to prevent its original algorithm drawbacks. The experimental analysis is carried out to demonstrate the efficiency of the designed coverage scheme in terms of various metrics, e.g. coverage rate, positioning errors, converge speed, and executed time. Compared experimental-result shows that the ATS scheme offers the WSN applicability coverage model to perform the deployment network application with excellent quality. Significantly, the coverage rate archived of the ATS is 87%, but the other methods are only below or equally 84% in the same comparison conditions.
In this study, we presented a Parameters-Optimized HBA (POHBA) to enhance the optimization performance of the HBA. The POHBA improves the network coverage rate of the Wireless sensor Network without increasing the alg...
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In this study, we presented a Parameters-Optimized HBA (POHBA) to enhance the optimization performance of the HBA. The POHBA improves the network coverage rate of the Wireless sensor Network without increasing the algorithm complexity by optimizing the parameters C and beta of the initial HBA. We defined the optimization rate (r_opt) for the first time to compare the optimization effect significantly of different algorithms or the same algorithm in different experimental scenarios. In our experiments, the optimization performance of POHBA is superior to the initial HBA. Meanwhile, we compared the performance of the POHBA, Grey Wolf Optimization (GWO) algorithm, and Particle Swarm Optimization (PSO) algorithm in four scenarios with identical experimental settings. In all simulation experiments, the most uniform network node distribution, the highest network coverage and optimization rate, and the best convergence performance were all obtained by POHBA. Especially in the large-scale network, POHBA kept excellent optimization performance. To identify the insight causes of why POHBA's performance is superior to GWO and PSO, we applied the dimension-wise diversity measurement for the first time, by which we found the best consistency in the ratios of exploration and exploitation and the highest proportion of the exploitation throughout the iterations obtained by POHBA, and that is the insight reason why an algorithm can get a superior optimization performance in our study.
In this paper, a fuzzy c-means clustering algorithm is proposed to determine the optimum deployment of sensornodes. It is for a given application space to improve energy efficiency and reduce cost. We performed simul...
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ISBN:
(纸本)9781936338290
In this paper, a fuzzy c-means clustering algorithm is proposed to determine the optimum deployment of sensornodes. It is for a given application space to improve energy efficiency and reduce cost. We performed simulation for building area to find minimum number and optimum location of sensornodes.
Wireless sensor network can act as a distributed sampling system in precision farming applications which aim at estimating the spatiotemporal *** nodes should be deployed referring to the communication range r and the...
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Wireless sensor network can act as a distributed sampling system in precision farming applications which aim at estimating the spatiotemporal *** nodes should be deployed referring to the communication range r and the sampling range r instead of the sensing *** this paper,a kind of systematic random deployment based on three popular regular patterns-equilateral triangle,square and hexagon is explored to achieve both coverage and *** efficiency of different regular patterns of systematic random deployment is also compared,thus enabling to make a better deployment decision for different values of r/r.
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