Nq-Gpls: N-Queen Inspired Gateway Placement And Learning Automata-Based Gateway Selection In Wireless Mesh Network

Keywords

Gateway placement; Gateway selection; Learning automata; Load balancing; Wireless Mesh Networks

Abstract

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.

Publication Date

11-21-2017

Publication Title

MobiWac 2017 - Proceedings of the 15th ACM International Symposium on Mobility Management and Wireless Access, Co-located with MSWiM 2017

Number of Pages

41-44

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/3132062.3132084

Socpus ID

85047971614 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85047971614

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