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NQ-GPLS: N-Queen Inspired Gateway Placement and Learning Automata-based Gateway Selection in Wireless Mesh Network
Conference proceeding   Open access

NQ-GPLS: N-Queen Inspired Gateway Placement and Learning Automata-based Gateway Selection in Wireless Mesh Network

Afsaneh Razi, Kien A. Hua and Akbar Majidi
Proceedings of the 15th ACM International Symposium on Mobility Management and Wireless Access, pp 41-44
21 Nov 2017
DOI: https://doi.org/10.1145/3132062.3132084
url
https://stars.library.ucf.edu/scopus2015/7374View
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Abstract

Networks -- Network algorithms -- Control path algorithms -- Network design and planning algorithms Networks -- Network algorithms -- Control path algorithms -- Traffic engineering algorithms Networks -- Network components -- Intermediate nodes Networks -- Network performance evaluation -- Network simulations Networks -- Network properties -- Network structure -- Network topology types -- Mesh networks -- Wireless mesh networks Networks -- Network protocols -- Network protocol design
This paper discusses two issues with multi-channel multi-radio Wireless Mesh Networks (WMN): gateway placement and gateway selection. To address these issues, a method will be proposed that places gateways at strategic locations to avoid congestion and adaptively learns to select a more efficient gateway for each wireless router by using learning automata. This method, called the N-queen Inspired Gateway Placement and Learning Automata-based Selection (NQ-GPLS), considers multiple metrics such as loss ratio, throughput, load at the gateways and delay. Simulation results from NS-2 simulator demonstrate that NQ-GPLS can significantly improve the overall network performance compared to a standard WMN.

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6 citations in Scopus

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