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An Efficient and Reliable Routing Method for Hybrid Mobile Ad Hoc Networks Using Deep Reinforcement Learning
Applied Bionics and Biomechanics ( IF 2.2 ) Pub Date : 2020-12-11 , DOI: 10.1155/2020/8888904
Murtadha M A Alkadhmi 1 , Osman N Uçan 1 , Muhammad Ilyas 1
Affiliation  

With the reliance of humans on mobile smart devices that have wireless communication, modules have significantly increased in recent years. Using these devices to communicate with the survivors during a disaster or its aftermath can significantly increase the chances of locating and saving them. Accordingly, a method is proposed in this study to extend the lifetime of the nodes in a Mobile Ad Hoc Network (MANET) while maintaining communications with the nearest base station (BS). Such a methodology allows the rapid establishment of temporary communications with these survivors, as restoring the complex infrastructure is a time-consuming process. The proposed method achieves the longer lifetime of the network by balancing the load throughout the nodes and avoids exhausting those with limited remaining energy. The proposed method has shown significant improvement in the lifetime of the MANET while maintaining similar Packet Delivery Rate (PDR) and route generation time, compared to existing methods.

中文翻译:

使用深度强化学习的混合移动自组织网络高效可靠的路由方法

随着人类对具有无线通信功能的移动智能设备的依赖,近年来模块数量显着增加。在灾难期间或灾后使用这些设备与幸存者进行通信可以显着增加定位和拯救他们的机会。因此,本研究提出了一种方法来延长移动自组织网络(MANET)中节点的寿命,同时保持与最近的基站(BS)的通信。这种方法允许与这些幸存者快速建立临时通信,因为恢复复杂的基础设施是一个耗时的过程。所提出的方法通过平衡整个节点的负载来实现更长的网络寿命,并避免耗尽剩余能量有限的节点。与现有方法相比,所提出的方法在保持相似的数据包传送率 (PDR) 和路由生成时间的同时,显着提高了 MANET 的生命周期。
更新日期:2020-12-11
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