Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
k-Center problems with minimum coverage
Theoretical Computer Science
Optimization models and methods for planning wireless mesh networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A gateway placement algorithm in wireless mesh networks
WICON '07 Proceedings of the 3rd international conference on Wireless internet
Ad Hoc and Neighborhood Search Methods for Placement of Mesh Routers in Wireless Mesh Networks
ICDCSW '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops
Wireless mesh networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
An Annealing Approach to Router Nodes Placement Problem in Wireless Mesh Networks
CISIS '10 Proceedings of the 2010 International Conference on Complex, Intelligent and Software Intensive Systems
Genetic Algorithms for Efficient Placement of Router Nodes in Wireless Mesh Networks
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
Wireless Mesh Networks: Current Challenges and Future Directions of Web-In-The-Sky
IEEE Wireless Communications
Local search methods for efficient router nodes placement in wireless mesh networks
Journal of Intelligent Manufacturing
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Node placement problems have been long investigated in the optimization field due to numerous applications in facility location, logistics, services, etc. Such problems are attracting again the attention of researchers now from the networking domain, and more especially from Wireless Mesh Networks (WMNs) field. Indeed, the placement of mesh routers nodes appears to be crucial for the performance and operability of WMNs, in terms of network connectivity and stability. However, node placement problems are known for their hardness in solving them to optimality, and therefore heuristics methods are approached to near-optimally solve such problems. In this work we evaluate the performance of different heuristic methods in order to judge on their suitability of solving mesh router nodes problem. We have selected methods from two different families, namely, local search methods (Hill Climbing and Simulated Annealing) and population-based methods (Genetic Algorithms). The former are known for their capability to exploit the solution space by constructing a path of visited solutions, while the later methods use a population of individuals aiming to largely explore the solution space. In both cases, a bi-objective optimization consisting in the maximization of the size of the giant component in the mesh routers network (for measuring network connectivity) and that of user coverage are considered. In the experimental evaluation, we have used a benchmark of instances--varying from small to large size--generated using different distributions of mesh node clients (Uniform, Normal, Exponential and Weibull).