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Coverage Hole Recovery Algorithm Based on Molecule Model in Heterogeneous WSNs

机译:基于分子模型的异构无线传感器网络覆盖孔恢复算法

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In diverse application fields, the increasing requisitions of Wireless Sensor Networks (WSNs) have more and more research dedicated to the question of sensor nodesa?? deployment in recent years. For deployment of sensor nodes, some key points that should be taken into consideration are the coverage area to be monitored, energy consumed of nodes, connectivity, amount of deployed sensors and lifetime of the WSNs. This paper analyzes the wireless sensor network nodes deployment optimization problem. Wireless sensor nodes deployment determines the nodesa?? capability and lifetime. For node deployment in heterogeneous sensor networks based on different probability sensing models of heterogeneous nodes, the author refers to the organic small molecule model and proposes a molecule sensing model of heterogeneous nodes in this paper. DSmT is an extension of the classical theory of evidence, which can combine with any type of trust function of an independent source, mainly concentrating on combined uncertainty, high conflict, and inaccurate source of evidence. Referring to the data fusion model, the changes in the network coverage ratio after using the new sensing model and data fusion algorithm are studied. According to the research results, the nodes deployment scheme of heterogeneous sensor networks based on the organic small molecule model is proposed in this paper. The simulation model is established by MATLAB software. The simulation results show that the effectiveness of the algorithm, the network coverage, and detection efficiency of nodes are improved, the lifetime of the network is prolonged, energy consumption and the number of deployment nodes are reduced, and the scope of perceiving is expanded. As a result, the coverage hole recovery algorithm can improve the detection performance of the network in the initial deployment phase and coverage hole recovery phase.
机译:在各种应用领域中,对无线传感器网络(WSN)的需求不断增长,越来越多的研究致力于传感器节点的问题。近年来部署。对于传感器节点的部署,应考虑的一些关键点是要监视的覆盖范围,节点的能耗,连接性,已部署传感器的数量以及WSN的寿命。本文分析了无线传感器网络节点部署优化问题。无线传感器节点的部署决定了节点能力和寿命。对于基于异构节点的不同概率感知模型的异构传感器网络中的节点部署,作者参考了有机小分子模型,提出了异构节点的分子感知模型。 DSmT是经典证据理论的扩展,可以与独立来源的任何类型的信任功能结合,主要集中于合并的不确定性,高冲突和不准确的证据来源。参照数据融合模型,研究了使用新的感知模型和数据融合算法后网络覆盖率的变化。根据研究结果,提出了基于有机小分子模型的异构传感器网络节点部署方案。通过MATLAB软件建立仿真模型。仿真结果表明,提高了算法的有效性,提高了网络覆盖率,提高了节点的检测效率,延长了网络的生命周期,降低了能耗和部署节点的数量,扩大了感知范围。结果,在初始部署阶段和覆盖漏洞恢复阶段,覆盖漏洞恢复算法可以提高网络的检测性能。

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