arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1105.6237cs.NI
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能量有效的多级异构无线传感器网络预测分簇算法

Energy efficient prediction clustering algorithm for multilevel heterogeneous wireless sensor networks

Tang Liu, Jian Peng, Jin Yang, Chunli Wang

摘要:

在设计无线传感器网络时,减少能量消耗、延长网络寿命是一个重要的问题。针对异构无线传感器网络,提出了一种新的能量和监测对象异构的模型。提出了一种适用于异构模型的节能预测聚类算法。该算法使节点根据能量和通信代价等因素选择簇头,从而使剩余能量较高的节点比剩余能量较低的节点有更高的概率成为簇头,使网络能量得到均匀耗散。为了减少分簇阶段广播时的能耗,延长网络生存时间,建立了规则数据采集节点的能耗预测模型。仿真结果表明,与现有的分簇算法相比,该算法能够获得更长的传感器网络生命周期、更高的能量效率和更优的网络监测质量。

英文摘要:

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. In this paper, a new model with energy and monitored objects heterogeneity is proposed for heterogeneous wireless sensor networks. We put forward an energy-efficient prediction clustering algorithm, which is adaptive to the heterogeneous model. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency and superior network monitoring quality.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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