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视觉传感器网络中节点感知模型为有向感知模型,感知范围被限定在节点的视野范围内.节点拥有多个感知方向,在一个工作时刻,节点只能工作于一个方向.针对视觉传感器网络的有向感知模型的点目标覆盖问题,提出一种贪婪算法(GreedyAlgorithm),在优化网络对于目标点覆盖的同时,解决了节点自身覆盖冲突的问题.在此基础上,引入“贡献率”概念反映节点在其感知方向上对于覆盖的贡献,提出了基于贡献率的贪婪算法(Contribution Rate Greedy Algorithm)以增大网络覆盖率.仿真实验表明了该算法的有效性.
The sensor perception model in the visual sensor network is a directional sensing model, and the perceived range is limited to the field of view of the nodes. The nodes have multiple sensing directions and the nodes can only work in one direction at one working moment. For the visual sensor networks This paper proposes a greedy algorithm (GreedyAlgorithm), which solves the problem of node coverage conflicts while optimizing the network coverage for the target points. On this basis, we introduce the concept of “contribution rate” In order to reflect the node’s contribution to coverage in its perceived direction, a contribution rate-based greedy algorithm (Contribution Rate Greedy Algorithm) is proposed to increase the network coverage. Simulation results show the effectiveness of the proposed algorithm.