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Node Placement in WMNs and Visualization of Evolutionary Computation Process Using WMN-GA System

Authors: Tetsuya Oda; Admir Barolli; Evjola Spaho; Leonard Barolli; Fatos Xhafa; Jiro Iwashige;

Node Placement in WMNs and Visualization of Evolutionary Computation Process Using WMN-GA System

Abstract

In Wireless Mesh Networks (WMNs), the performance of the network is affected by the location of mesh nodes. The placement of mesh nodes is an important design issue in deploying such networks. For a given grid size and a given number of mesh nodes, we use Genetic Algorithms (GAs) to find where to position the mesh nodes in order to maximize the coverage and the connectivity of the network. In this paper, we use WMN-GA system for node placement problem in WMNs. We evaluate and compare the performance of Normal and Uniform distributions considering giant component and number of covered users parameters. For both scenarios, we present the visualization of evolutionary computation process. The simulation results show that Normal distribution offers better coverage compared with Uniform distribution for the same selection method, crossover and mutation rate and population size. The visualization of evolutionary process show that in the Normal distribution, the client nodes are located near the center of the grid. Since these nodes are near each other, a mesh router can cover many clients so for Normal distribution the system has better performance.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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