Abstract
A proper design of Wireless Mesh Networks (WMNs) is a fundamental task that should be addressed carefully to allow the deployment of scalable and efficient networks. Specifically, choosing strategic locations to optimally place gateways prior to network deployment can alleviate a number of performance/scalability related problems. In this paper, we first, propose a novel clustering based gateway placement algorithm (CBGPA) to effectively select the locations of gateways. Existing solutions for optimal gateway placement using clustering approaches are tree-based and therefore are inherently less reliable since a tree topology uses a smaller number of links. Independently from the tree structure, CBGPA strategically places the gateways to serve as many routers as possible that are within a bounded number of hops. Next, we devise a new multi-objective optimization approach that models WMN topologies from scratch. The three objectives of deployment cost, network throughput and average congestion of gateways are simultaneously optimized using a nature inspired meta-heuristic algorithm coupled with CBGPA. This provides the network operator with a set of bounded-delay trade-off solutions. Comparative simulation studies with different key parameter settings are conducted to show the effectiveness of CBGPA and to evaluate the performance of the proposed model.
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