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Hybrid Optimize Strategy based QoS Route Algorithm for Mobile Ad hoc Networks | Science Publications

机译:Ad Hoc网络中基于混合优化策略的QoS路由算法|科学出版物

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> It is very difficult to find feasible QoS (Quality of service) routes in the mobile ad hoc networks (MANETs), because of the nature constrains of it, such as dynamic network topology, wireless communication link and limited process capability of nodes. In order to reduce average cost in flooding path discovery scheme of the traditional MANETs routing protocols and increase the probability of success in finding QoS feasible paths and we proposed a heuristic and distributed route discovery method named RLGAMAN that supports QoS requirement for MANETs in this study. This method integrates a distributed route discovery scheme with a reinforcement learning (RL) method that only utilizes the local information for the dynamic network environment; and the route expand scheme based on genetic algorithms (GA) method to find more new feasible paths and avoid the problem of local optimize. We investigate the performance of the RLGAMAN by simulation experiment bed in NS2. Compared with traditional method, the experiment results showed the network performance is improved obviously and RLGAMAN is efficient and effective.
机译: >在移动自组织网络(MANET)中很难找到可行的QoS(服务质量)路由,因为它的性质受到限制,例如动态网络拓扑,无线通信链路和受限节点的处理能力。为了减少传统MANETs路由协议的泛洪路径发现方案中的平均成本,并增加成功找到QoS可行路径的可能性,我们在研究中提出了一种启发式的分布式路由发现方法RLGAMAN,该方法支持MANET的QoS要求。该方法将分布式路由发现方案与仅用于动态网络环境的本地学习的强化学习(RL)方法集成在一起。提出了一种基于遗传算法的路由扩展方案,以寻找更多的可行路径,避免了局部优化的问题。我们通过在NS2中的仿真实验台来研究RLGAMAN的性能。实验结果表明,与传统方法相比,RLGAMAN的网络性能有了明显的提高,并且有效且有效。

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