A weighted coding in a genetic algorithm for the degree-constrained minimum spanning tree problem
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
Optimization models and methods for planning wireless mesh networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Wireless mesh networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
On some current results of graph theory for ad-hoc networks
Journal of Mobile Multimedia
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
DMesh: Incorporating Practical Directional Antennas in Multichannel Wireless Mesh Networks
IEEE Journal on Selected Areas in Communications
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The optimal placement of mesh nodes of an infrastructure wireless mesh network is considered. The optimization is performed w.r.t. two objectives, i.e. installation cost and coverage probability. Mesh nodes with directional antennae are assumed. In this regard, we propose MOGAMESH, a 2-stages multi-objective evolutionary optimization algorithm which tries to optimize the two objectives by means of genetic algorithms, where individuals or solutions are represented by network graphs. In the first stage, candidate network topologies are found by letting a population of graphs evolve. Iteratively, a non-dominated sorting technique classifies individuals which are then selected for the evolution process. Solutions are individuals belonging to the Pareto front, i.e. the set of all non-dominated solutions. In the second stage, a link elimination algorithm further reduces the number of links of the network. In this way, MOGAMESH can provide the network designer with the maximum number of devices to install for every mesh node along with candidate network topologies. We analyze the performance of MOGAMESH for realistic instances of a wireless mesh network with increasing user density.