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首页> 外文期刊>International Journal on Applications of Graph Theory in Wireless ad hoc Networks and Sensor Networks >Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks
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Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks

机译：无线传感器网络中基于覆盖和连通性的神经网络节能路由

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摘要

There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
机译：在设计和部署无线传感器网络（WSN）时面临许多挑战。关键挑战之一是如何充分利用有限的能量来延长网络寿命，因为能量是无线传感器网络中的宝贵资源。部署网络后，应持续监控能耗状态。在本文中，我们提出了在WSN中基于覆盖和连接感知的神经网络的节能路由，目的是最大化网络寿命。在提出的方案中，问题被表述为具有覆盖和连通性约束的线性规划（LP）。提出了使用神经网络中的自适应学习，然后进行覆盖和具有数据传输的连通性感知路由的簇首选择。就诸如活动节点数，分组传送分数和节点剩余能量之类的参数，将所提出的方案与现有方案进行比较。仿真结果表明，该方案可以在无线传感器网络中广泛应用。

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