Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

Kala, S M and Musham, R and Reddy, M P K and Tamma, Bheemarjuna Reddy (2015) Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), 10-13 August, 2015, Kochi, India.

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Abstract

The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network per- formance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitiga tion is a primary design objective in WMNs. Interference alleviati on is often effected through efficient channel allocation (CA) sc hemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. Howe ver, numerous CA schemes have been proposed in research literatu re and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. I n this work, we propose a reliable interference estimation an d CA performance prediction approach. We demonstrate its effica cy by substantiating the CA performance predictions for a given W MN with experimental data obtained through rigorous simulati ons on an ns-3 802.11g environment.

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IITH Creators:
IITH CreatorsORCiD
Tamma, Bheemarjuna ReddyUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: CA scheme, MRMC, NS-3 802.11g environment, WMN, channel assignment prediction reliability, interference alleviation, interference estimation, interference mitigation, multiradio multichannel, wireless mesh network
Subjects: Computer science > Special computer methods
Computer science > Big Data Analytics
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 24 Aug 2015 05:52
Last Modified: 07 Sep 2017 09:50
URI: http://raiith.iith.ac.in/id/eprint/1874
Publisher URL:
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