NQ-GPLS: N-Queen Inspired Gateway Placement and Learning Automata-Based Gateway Selection in Wireless Mesh Network
| Title | NQ-GPLS: N-Queen Inspired Gateway Placement and Learning Automata-Based Gateway Selection in Wireless Mesh Network |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Razi, Afsaneh, Hua, Kien A., Majidi, Akbar |
| Conference Name | Proceedings of the 15th ACM International Symposium on Mobility Management and Wireless Access |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5163-8 |
| Keywords | composability, gateway placement, gateway selection, learning automata, load balancing., Metrics, pubcrawl, resilience, Resiliency, 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. |
| URL | https://dl.acm.org/citation.cfm?doid=3132062.3132084 |
| DOI | 10.1145/3132062.3132084 |
| Citation Key | razi_nq-gpls:_2017 |