2021
DOI: 10.1007/978-3-030-70572-5_3
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A Multi-objective Approach for Wireless Heterogeneous Router Placement in Rural Wireless Mesh Networks

Abstract: The design of a wireless mesh network is usually posed as a multi-objective optimization problem. In this paper, we consider the planning of a wireless mesh network in a rural region where the network coverage and the cost of the architecture must be optimized. In addition, mesh routers are heterogeneous, meaning that they may have different transmission ranges. In the network model, we assume that the region to serve is divided into a set of small zones of various types, including cost-effective locations and… Show more

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Cited by 3 publications
(2 citation statements)
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“…There are also some approaches for mesh router placement optimization that combine several meta-heuristics, clustering algorithms, or other methods. In [ 26 ], the authors proposed Multi-objective Simulated Annealing based Centre of Mass (MCM) as a mesh router placement optimization method and Multi Objective Simulated Annealing based Centre of Mass (MSAC), which combines SA and MCM. They showed that MSAC achieves a better tradeoff between WMN coverage and cost because it does not consider min–max regret values for many large instances and in most cases provides a good Pareto front.…”
Section: Related Workmentioning
confidence: 99%
“…There are also some approaches for mesh router placement optimization that combine several meta-heuristics, clustering algorithms, or other methods. In [ 26 ], the authors proposed Multi-objective Simulated Annealing based Centre of Mass (MCM) as a mesh router placement optimization method and Multi Objective Simulated Annealing based Centre of Mass (MSAC), which combines SA and MCM. They showed that MSAC achieves a better tradeoff between WMN coverage and cost because it does not consider min–max regret values for many large instances and in most cases provides a good Pareto front.…”
Section: Related Workmentioning
confidence: 99%
“…Heuristic systems tend to be more historic, and although recent work was carried out on clustering algorithms for MRs [35] and in tree-based approaches [36], it otherwise tends to focus on gateway placement. Meta-heuristics-based techniques have proven the most popular, and recent studies [37,38] have focused on using hill-climbing and simulated annealing (SA), respectively, for MR router placement through various environments.…”
Section: Topology Optimisationmentioning
confidence: 99%