RL-based routing in biomedical mobile wireless sensor networks using trust and reputation

Yanee Naputta, W. Usaha
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引用次数: 11

Abstract

The main function of biomedical sensor network is to guarantee that the data packets from patients can be delivered reliably to the destination node or medical center. Attached to patients, these nodes can be mobile, thus forming a mobile wireless sensor network (mWSN). Moreover, non-cooperative nodes may also be present in the network. This paper therefore proposes a routing method for non-cooperative mWSNs based on Reinforcement Learning (RL). In particular, a reputation and trust scheme to avoid misbehaving nodes was integrated with an existing RL-based routing protocol called RL-QRP. We evaluated its performance in non-cooperative mWSNs under various conditions of non-cooperation and mobility. We found that the proposed method can achieve a success ratio of up to 11% over the RL-QRP, and 25% over a non-learning brute force search threshold method.
基于rl的基于信任和声誉的生物医学移动无线传感器网络路由
生物医学传感器网络的主要功能是保证来自患者的数据包能够可靠地传递到目的节点或医疗中心。这些节点连接到患者身上,可以移动,从而形成一个移动无线传感器网络(mWSN)。此外,网络中也可能存在非合作节点。因此,本文提出了一种基于强化学习(RL)的非合作多wsn路由方法。特别是,为了避免行为不端的节点,将信誉和信任方案与现有的基于rl的路由协议RL-QRP集成在一起。在不同的非合作和移动条件下,对其在非合作mWSNs中的性能进行了评价。我们发现,与RL-QRP相比,该方法的成功率高达11%,与非学习性蛮力搜索阈值方法相比,成功率高达25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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