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An Adaptive Clustering Algorithm with Power Control in Wireless Sensor Networks

机译:无线传感器网络中功率控制的自适应聚类算法

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We propose an adaptive clustering algorithm with power control, ACA-PC, that chooses adaptive clusters and controls transmission power levels in order to minimize the total energy consumption of the sensor networks and maximize the amount of transmission data Our core concepts are zone division and dynamic power control. A sensor network is divided into n zones based on geographical information. A large number of nodes bring about collision of data transmission. According to node density, a zone can be divided into two sub-zones or merged with other zone. The close neighbor nodes are grouped by a cluster in its zone. Therefore, we control the transmission power level of the common nodes in the same cluster to avoid collision with other clusters. Using network simulator (NS-2), we verify that ACA-PC can conserve the energy of sensors and prolong the lifetime of sensor networks better than other proposed algorithms.
机译:我们提出了一种具有功率控制,ACA-PC的自适应聚类算法,可选择自适应集群并控制传输功率电平,以便最小化传感器网络的总能量消耗并最大限度地提高我们的核心概念的传输数据量是区域划分和动态功率控制。根据地理信息,传感器网络分为n个区域。大量节点带来了数据传输的碰撞。根据节点密度,区域可以分为两个子区域或与其他区域合并。 Close邻居节点由其区域中的群集分组。因此,我们控制同一群集中的公共节点的传输功率电平,以避免与其他集群冲突。使用网络模拟器(NS-2),我们验证了ACA-PC是否可以节省传感器的能量,并延长比其他提出的算法更好的传感器网络的寿命。

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