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Performance evaluation considering iterations per phase and SA temperature in WMN-SA system

Performance evaluation considering iterations per phase and SA temperature in WMN-SA system One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider Simulated Annealing Algorithm (SA) temperature and Iteration per phase for the router node placement problem in WMNs. We want to find the optimal distribution of router nodes in order to provide the best network connectivity and provide the best coverage in a set of Normal distributed clients. From simulation results, we found how to optimize both the size of Giant Component and number of covered mesh clients. When the number of iterations per phase is big, the performance is better in WMN-SA System. From for SA temperature, when SA temperature is 0 and 1, the performance is almost same. When SA temperature is 2 and 3 or more, the performance decrease because there are many kick ups. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mobile Information Systems IOS Press

Performance evaluation considering iterations per phase and SA temperature in WMN-SA system

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References (17)

Publisher
IOS Press
Copyright
Copyright © 2014 by IOS Press, Inc
ISSN
1574-017x
eISSN
1875-905X
DOI
10.3233/MIS-130187
Publisher site
See Article on Publisher Site

Abstract

One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider Simulated Annealing Algorithm (SA) temperature and Iteration per phase for the router node placement problem in WMNs. We want to find the optimal distribution of router nodes in order to provide the best network connectivity and provide the best coverage in a set of Normal distributed clients. From simulation results, we found how to optimize both the size of Giant Component and number of covered mesh clients. When the number of iterations per phase is big, the performance is better in WMN-SA System. From for SA temperature, when SA temperature is 0 and 1, the performance is almost same. When SA temperature is 2 and 3 or more, the performance decrease because there are many kick ups.

Journal

Mobile Information SystemsIOS Press

Published: Jan 1, 2014

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