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Optimizing infrastructure placement in Wireless Mesh Networks

Nawaf, Liqaa 2017. Optimizing infrastructure placement in Wireless Mesh Networks. PhD Thesis, Cardiff University.
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Abstract

Wireless Mesh Networks (WMNs) are a promising flexible and low cost technology to efficiently deliver broadband services to communities. In a WMN, a mesh router is deployed at each house, which acts both as a local access point and a relay to other nearby houses. Since mesh routers typically consist of off-the-shelf equipment, the major cost of the network is in the placement and management of Internet Transit Access Points (ITAP) which act as the connection to the internet. In designing a WMN, we therefore aimed to minimize the number of ITAPs required whilst maximizing the traffic that could be served to each house. We investigated heuristic and meta-heuristic approaches with an efficient combination of move operators to solve these placement problems by using single and multi-objective formulations. Many real-world optimisation problems involve dealing with multiple and sometimes conflicting objectives. A multi-objective approach to optimize WMN infrastructure placement design with three conflicting objectives is presented: it aims to minimize the number of ITAPs, maximize the fairness of bandwidth allocation and maximize the coverage to mesh clients. We discuss how such an approach could allow more effective ITAP deployment, enabling a greater number of consumers to obtain internet services. Two approaches are compared during our investigation of multi-objective optimization, namely the weighted sum approach and the use of an evolutionary algorithm. In this thesis we investigate a multi-objective optimization algorithm to solve the WMN infrastructure placement problem. The move operators demonstrate their efficiency when compared to simple Hill Climbing (HC) and Simulated Annealing (SA) for the single objective method.

Item Type: Thesis (PhD)
Status: Unpublished
Schools: Computer Science & Informatics
Date of First Compliant Deposit: 30 May 2017
Last Modified: 04 Jun 2017 09:51
URI: http://orca-mwe.cf.ac.uk/id/eprint/100966

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