Graphical abstractDisplay Omitted HighlightsThe present work proposes a Modified Non-dominated Sorting Genetic Algorithm-II which is applied to the routing problem in WMN.Dynamic crowding distance strategy aims to improve the diversity of the non-dominated solution.Analytic hierarchy process is used to find the best compromise solution.Compared to NSGA-II, the proposed algorithm can improve the throughput and minimizes the transmission delay. 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.
['R. Murugeswari', 'S. Radhakrishnan', 'D. Devaraj']
A multi-objective evolutionary algorithm based QoS routing in wireless mesh networks