Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
Routing in multi-radio, multi-hop wireless mesh networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Optimizing the Placement of Internet TAPs in Wireless Neighborhood Networks
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Comparison and evaluation of multiple objective genetic algorithms for the antenna placement problem
Mobile Networks and Applications
An effective use of crowding distance in multiobjective particle swarm optimization
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Proceedings of the 11th annual international conference on Mobile computing and networking
Long distance wireless mesh network planning: problem formulation and solution
Proceedings of the 16th international conference on World Wide Web
MOPSO: a proposal for multiple objective particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Throughput-coverage tradeoff in a scalable wireless mesh network
Journal of Parallel and Distributed Computing
Performance model for IEEE 802.11s wireless mesh network deployment design
Journal of Parallel and Distributed Computing
Survivable and delay-guaranteed backbone wireless mesh network design
Journal of Parallel and Distributed Computing
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
IEEE Transactions on Evolutionary Computation
Automatic mesh generation for mobile network dimensioning using evolutionary approach
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Intelligent content aware services in 3G wireless networks
IEEE Journal on Selected Areas in Communications
Gateway Placement Optimization in Wireless Mesh Networks With QoS Constraints
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.24 |
Existing approaches for optimal planning of wireless mesh networks (WMNs) deployment revolves around the deployment cost as the pivotal concept to optimize. In this paper, we adopt a new approach to optimize the planning of WMNs that guarantees an acceptable level of network performance prior to its deployment. It is a simultaneous optimization process of network deployment cost and network throughput objectives while taking into account all the parameters that have a significant impact on the network efficiency. We propose three multi-objective models for WMN planning problem, namely Load-Balanced Model, Interference Model, and Flow-Capacity Model. We devise an evolutionary swarm-based algorithm that is a hybrid combination of multi-objective Particle Swarm Optimization (MOPSO) and Genetic Algorithms (GAs) to solve the three models. We use realistic network sizes (up to 100 mesh nodes) to perform a thorough comparative experimental study on these three instance models with different key-parameter settings. Finally, we use the network simulator OMNET++ to evaluate the three models in terms of the actual performance (network throughput). The results presented in this paper show that Load-Balanced Model totally supersedes the Flow-Capacity Model and performs better than the Interference Model.