基于分形维数的无线传感器网络低能量算法

C. Fan, Ting Dong, Z. Wen, Qiong Wu
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引用次数: 3

摘要

提出了一种基于网络分形维数计算的无线传感器网络优化算法(LEA算法),旨在解决节点能量限制和节点能量消耗不平衡的问题。与LEA算法相比,该算法基于长距离依赖模型(PFM模型)和短程相关模型(TIAF模型),其中PFM模型和TIAF模型分别与网络结构维数和网络数据流维数相关,优化算法不仅一轮计算每个集群或子网维数,以确定哪个维数高于阈值,然后进行更改;同时计算数据流维数,以便选择更好的数据传输路径。网络结构和数据流的维数计算方法有简单分形和多重分形两种。仿真结果表明,与传统方法相比,该方法能更有效地延长网络寿命和节点工作时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A low energy algorithm of wireless sensor networks based on fractal dimension
An optimization algorithm (LEA algorithm) of wireless sensor networks based on network fractal dimension calculation is proposed and intended to tackle energy limitation of nodes and their imbalanced energy consumption. Compared with LEA algorithm about the energy consumption, which is based on both long range dependence model (PFM model) and short range related model (TIAF model), where PFM and TIAF model are related to network structure dimension and network data flow dimension respectively, the Optimization algorithm not only calculates each cluster or sub-networks dimension in one round in order to decide which dimension is higher than the threshold and then makes changes, but also calculates data flow dimension in order to select a better route for data transmission. The methods of dimension calculation for network structure and data flow are simply fractal and multifractal. Simulation results show that the proposed method can more effectively lengthen the network lifetime and nodes working hours than the traditional methods.
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