Genetic algorithm approach for QoS-based tree topology construction in IEEE 802.16 mesh networks
(2013) In Science China Information Sciences 56(3). p.1-17- Abstract
- The topological characteristics of an IEEE 802.16 mesh network including the tree’s depth and degree of its nodes affect the delay and throughput of the network. To reach the desired trade-off between delay and throughput, all potential trees should be explored to obtain a tree with the proper topology. Since the number of extractable tree topologies from a given network graph is enormous, we use a genetic algorithm (GA) to explore the search space and find a good enough trade-off between per-node, as well as network-wide delay and throughput. In the proposed GA approach, we use the Pruefer code tree representation followed by novel genetic operators. First, for each individual tree topology, we obtain expressions analytically for per-node... (More)
- The topological characteristics of an IEEE 802.16 mesh network including the tree’s depth and degree of its nodes affect the delay and throughput of the network. To reach the desired trade-off between delay and throughput, all potential trees should be explored to obtain a tree with the proper topology. Since the number of extractable tree topologies from a given network graph is enormous, we use a genetic algorithm (GA) to explore the search space and find a good enough trade-off between per-node, as well as network-wide delay and throughput. In the proposed GA approach, we use the Pruefer code tree representation followed by novel genetic operators. First, for each individual tree topology, we obtain expressions analytically for per-node delay and throughput. Based on the required quality of service, the obtained expressions are invoked in the computation of fitness functions for the genetic approach. Using a proper fitness function, the proposed algorithm is able to find the intended trees while different constraints on delay and throughput of each node are imposed. Employing a GA approach leads to the exploration of this extremely wide search space in a reasonably short time, which results in overall scalability and accuracy of the proposed tree exploration algorithm. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8056712
- author
- Yousefi, Saleh ; Bastani, Saeed LU ; Mazoochi, Mojtaba and Ghiamatyoun, Alireza
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Science China Information Sciences
- volume
- 56
- issue
- 3
- pages
- 1 - 17
- publisher
- SP Science China Press
- external identifiers
-
- scopus:84871816911
- ISSN
- 1009-2757
- DOI
- 10.1007/s11432-012-4735-z
- language
- English
- LU publication?
- no
- id
- 87eeed04-2679-4ceb-9743-9f9d077544ed (old id 8056712)
- date added to LUP
- 2016-04-01 14:51:18
- date last changed
- 2022-01-28 02:53:22
@article{87eeed04-2679-4ceb-9743-9f9d077544ed,
abstract = {{The topological characteristics of an IEEE 802.16 mesh network including the tree’s depth and degree of its nodes affect the delay and throughput of the network. To reach the desired trade-off between delay and throughput, all potential trees should be explored to obtain a tree with the proper topology. Since the number of extractable tree topologies from a given network graph is enormous, we use a genetic algorithm (GA) to explore the search space and find a good enough trade-off between per-node, as well as network-wide delay and throughput. In the proposed GA approach, we use the Pruefer code tree representation followed by novel genetic operators. First, for each individual tree topology, we obtain expressions analytically for per-node delay and throughput. Based on the required quality of service, the obtained expressions are invoked in the computation of fitness functions for the genetic approach. Using a proper fitness function, the proposed algorithm is able to find the intended trees while different constraints on delay and throughput of each node are imposed. Employing a GA approach leads to the exploration of this extremely wide search space in a reasonably short time, which results in overall scalability and accuracy of the proposed tree exploration algorithm.}},
author = {{Yousefi, Saleh and Bastani, Saeed and Mazoochi, Mojtaba and Ghiamatyoun, Alireza}},
issn = {{1009-2757}},
language = {{eng}},
number = {{3}},
pages = {{1--17}},
publisher = {{SP Science China Press}},
series = {{Science China Information Sciences}},
title = {{Genetic algorithm approach for QoS-based tree topology construction in IEEE 802.16 mesh networks}},
url = {{http://dx.doi.org/10.1007/s11432-012-4735-z}},
doi = {{10.1007/s11432-012-4735-z}},
volume = {{56}},
year = {{2013}},
}