Title
Node Placement in WMNs for Different Movement Methods: A Hill Climbing System Considering Exponential and Weibull Distributions
Abstract
In this paper, we used our proposed and implemented system based on Hill Climbing algorithm, called WMN-HC for mesh router node placement in WMNs. We evaluate and compare the performance of the proposed system for different movement methods. We took into consideration Exponential and Weibull distributions of mesh clients. We use as evaluation metrics giant component and number of covered mesh clients. We compare the performance of WMN-HC for Exponential and Weibull distribution of mesh clients and different movement methods. The simulation results show that, the performance of the four different movement methods depend on the distribution of mesh client nodes. For Exponential distribution of mesh clients, the WMN-HC achieves good performance for Combination, Radius and Swap movement methods. For Weibull distribution of mesh clients, the WMN-HC has the best solution when the movement method is the Swap. The Random movement method has the worst performance among other movement methods.
Year
DOI
Venue
2014
10.1109/BWCCA.2014.53
BWCCA
Keywords
Field
DocType
hill climbing system,hill climbing,random processes,metrics giant component evaluation,random movement method,wireless mesh networks, hill climbing, node placement, connectivity, coverage,swap movement method,coverage,wireless mesh networks,wireless mesh network,node placement,mesh router node placement,wmn,radius movement method,telecommunication network routing,combination movement method,weibull distribution,connectivity,exponential distribution,wireless communication,simulation,ad hoc networks
Hill climbing,Wireless,Exponential function,Computer science,Computer network,Weibull distribution,Giant component,Exponential distribution,Router,Wireless ad hoc network,Distributed computing
Conference
Citations 
PageRank 
References 
0
0.34
12
Authors
6
Name
Order
Citations
PageRank
Xinyue Chang1113.42
Shinji Sakamoto235641.07
Tetsuya Oda344586.37
Makoto Ikeda41202207.10
Leonard Barolli514022.02
Fatos Xhafa63433343.33