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Mining Historical Data towards Interference Management in Wireless SDNs

Karimi, Maryam and Krishnamurthy, PV and Joshi, J and Tipper, David (2017) Mining Historical Data towards Interference Management in Wireless SDNs. Q2SWinet '17: Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks.

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WiFi networks are often planned to reduce interference through planning, macroscopic self-organization (e.g. channel switching) or network management. In this paper, we explore the use of historical data to automatically predict traffic bottlenecks and make rapid decisions in a wireless (WiFi-like) network on a smaller scale. This is now possible with software defined networks (SDN), whose controllers can have a global view of traffic flows in a network. Models such as classification trees can be used to quickly make decisions on how to manage network resources based on the quality needs, service level agreement or other criteria provided by a network administrator. The objective of this paper is to use data generated by simulation tools to see if such classification models can be developed and to evaluate their efficacy. For this purpose, extensive simulation data were collected and data mining techniques were then used to develop QoS prediction trees. Such trees can predict the maximum delay that results due to specific traffic situations with specific parameters. We evaluated these decision/classification trees by placing them in an SDN controller. OpenFlow cannot directly provide the necessary information for managing wireless networks so we used POX messenger to set up an agent on each AP for adjusting the network. Finally we explored the possibility of updating the tree using feedback that the controller receives from hosts. Our results show that such trees are effective and can be used to manage the network and decrease maximum packet delay.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Krishnamurthy, PVprashk@pitt.eduPRASHK
Joshi, Jjjoshi@pitt.eduJJOSHI
Tipper, Daviddtipper@pitt.eduDTIPPER
Date: 21 November 2017
Date Type: Publication
Journal or Publication Title: Q2SWinet '17: Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks
Publisher: ACM
DOI or Unique Handle: 10.1145/3132114.3132125
Schools and Programs: School of Computing and Information > Telecommunications
Refereed: Yes
Article Type: Research Article
Date Deposited: 05 Jul 2018 19:19
Last Modified: 05 Jul 2018 19:19


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