DocumentCode :
2288188
Title :
Using data mining to study the impact of topology characteristics on the performance of wireless mesh networks
Author :
Calçada, Tânia ; Cortez, Paulo ; Ricardo, Manuel
Author_Institution :
Fac. de Eng., Univ. do Porto, Porto, Portugal
fYear :
2012
fDate :
1-4 April 2012
Firstpage :
1725
Lastpage :
1730
Abstract :
This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE 802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighborhood of the gateway, and the hidden nodes in the neighborhood of the gateway. Network performance metrics are throughput, fairness and delay. The data mining Support Vector Machine (SVM) model was used to extract the relationships between the network topology metrics and the network performance metrics based on data results obtained through ns-2 simulation of random networks. The results obtained can be used as a basis to design channel assignment algorithms or to aid the deployment and management of single radio wireless mesh networks.
Keywords :
channel allocation; data mining; internetworking; network servers; support vector machines; telecommunication network management; telecommunication network topology; wireless channels; wireless mesh networks; NS-2 simulation; channel assignment algorithm; data mining SVM model; data mining support vector machine model; gateway neighborhood node density; hidden node; hop count; network performance metric; single radio multichannel IEEE 802.11 mesh network; single radio wireless mesh network topology; subnetwork node; Aggregates; Data models; Logic gates; Measurement; Network topology; Throughput; Topology; Mesh networks; SVM; channel assignment; data mining; hidden nodes; miss ratio; multi-channel; node density; relative importance; single-radio; topology metrics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications and Networking Conference (WCNC), 2012 IEEE
Conference_Location :
Shanghai
ISSN :
1525-3511
Print_ISBN :
978-1-4673-0436-8
Type :
conf
DOI :
10.1109/WCNC.2012.6214062
Filename :
6214062
Link To Document :
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