With the advancement of Internet of Things (IoT), the devices are allowed to interact with other networks like mobile ad hoc network (MANET). The MANET‐IoT systems often undergo energy balancing problem between the sensor nodes, whereas the MANETs operate on mobile sensor nodes. Hence, proper utilization of battery power is required to maintain the network connectivity during a multi‐hop transmission. In this paper, we propose a DeepSense IoT‐MANET framework that effectively routes the packets from the IoT nodes via mobile sensor nodes in MANETs. The routings between the MANETs are organized by DeepSense interconnected with deep neural network (DNN) learning methods. The performance of the DeepSense DNN method is evaluated against various network metrics to evaluate the efficacy of the model.

中文翻译：

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DeepSense-深度神经网络框架，可改善IoT‐MANET的网络寿命

随着物联网（IoT）的发展，设备可以与其他网络（如移动自组织网络（MANET））进行交互。MANET-IoT系统通常会在传感器节点之间遇到能量平衡问题，而MANET在移动传感器节点上运行。因此，在多跳传输期间需要适当利用电池电量以维持网络连接性。在本文中，我们提出了DeepSense IoT‐MANET框架，该框架可通过MANET中的移动传感器节点有效地路由来自IoT节点的数据包。MANET之间的路由由与深度神经网络（DNN）学习方法互连的DeepSense组织。针对各种网络指标评估了DeepSense DNN方法的性能，以评估模型的有效性。