Department of Basic and Applied Sciences, Arab Academy for Science, Technology and Maritime Transport, Cairo, Egypt.
Department of Electronics and Communications, Arab Academy for Science, Technology and Maritime Transport, Cairo, Egypt.
PLoS One. 2018 Mar 6;13(3):e0193142. doi: 10.1371/journal.pone.0193142. eCollection 2018.
A mobile ad hoc network is a conventional self-configuring network where the routing optimization problem-subject to various Quality-of-Service (QoS) constraints-represents a major challenge. Unlike previously proposed solutions, in this paper, we propose a memetic algorithm (MA) employing an adaptive mutation parameter, to solve the multicast routing problem with higher search ability and computational efficiency. The proposed algorithm utilizes an updated scheme, based on statistical analysis, to estimate the best values for all MA parameters and enhance MA performance. The numerical results show that the proposed MA improved the delay and jitter of the network, while reducing computational complexity as compared to existing algorithms.
移动自组网是一种常规的自配置网络,其中路由优化问题(受到各种服务质量(QoS)约束的限制)是一个主要挑战。与以前提出的解决方案不同,在本文中,我们提出了一种使用自适应变异参数的遗传算法(MA),以解决具有更高搜索能力和计算效率的组播路由问题。所提出的算法利用基于统计分析的更新方案来估计所有 MA 参数的最佳值,并提高 MA 的性能。数值结果表明,与现有算法相比,所提出的 MA 改善了网络的延迟和抖动,同时降低了计算复杂度。