A multi-objective evolutionary algorithm based QoS routing in wireless mesh networks |
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| Affiliation: | 1. Department of Computer Science and Engineering, Kalasalingam University, Krishnankoil 626 126, Tamilnadu, India;2. Department of Electrical and Electronic Engineering, Kalasalingam University, Krishnankoil 626 126, Tamilnadu, India;1. Federal University of Technology (UTFPR), Elect. Eng. Dept., Av. Alberto Carazzai, 1640, 86300-000 Cornélio Procópio, PR, Brazil;2. Federal University of São Carlos (UFSCAR), Rodovia Washington Luís, km 235 – SP 310, 13565-905 São Carlos, SP, Brazil;1. School of Software Engineering, Chongqing University, Chongqing 400044, PR China;2. School of Computing, National University of Singapore, Singapore 117417, Singapore;3. School of Information Science and Engineering, Lanzhou University, Gansu 730000, PR China;4. Faculty of Computer and Information Science, Southwest University, Chongqing 400715, PR China;5. Faculty of Engineering, The University of Sydney, Sydney 2006, Australia;1. Materials Processing Simulation Laboratory (MPS-LAB), School of Materials Science and Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran;2. Reservoir Engineering Systems, Petroleum Engineering Dept., Main Office Building of National Iranian South Oil Company (NISOC), Ahvaz, Iran;1. School of Computer and Software Engineering, Xihua University, Chengdu 610039, China;2. School of Digital Media, Jiangnan University, Wuxi 214122, China;1. Institute for High Performance Computing and Networking, National Research Council of Italy, CNR-ICAR, Via P. Bucci 41C, 87036 Rende (CS), Italy;2. Department of Mathematics and Computer Science, Universitá degli Studi di Palermo, 90123 Palermo, via Archirafi 34, Italy |
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| Abstract: | The huge demand for real time services in wireless mesh networks (WMN) creates many challenging issues for providing quality of service (QoS). Designing of QoS routing protocols, which optimize the multiple objectives is computationally intractable. This paper proposes a new model for routing in WMN by using Modified Non-dominated Sorting Genetic Algorithm-II (MNSGA-II). The objectives which are considered here are the minimization of expected transmission count and the transmission delay. In order to retain the diversity in the non-dominated solutions, dynamic crowding distance (DCD) procedure is implemented in NSGA-II. The simulation is carried out in Network Simulator 2 (NS-2) and comparison is made using the metrics, expected transmission count and transmission delay by varying node mobility and by increasing number of nodes. It is observed that MNSGA-II improves the throughput and minimizes the transmission delay for varying number of nodes and higher mobility scenarios. The simulation clearly shows that MNSGA-II algorithm is certainly more suitable for solving multiobjective routing problem. A decision-making procedure based on analytic hierarchy process (AHP) has been adopted to find the best compromise solution from the set of Pareto-solutions obtained through MNSGA-II. The performance of MNSGA-II is compared with reference point based NSGA-II (R-NSGA-II) in terms of spread. |
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| Keywords: | Dynamic crowding distance Multiobjective optimization Partial mapped crossover Analytic hierarchy process |
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