一种基于非均匀分簇的低能耗安全数据融合方法

A Low Energy-Consuming Private Data Aggregation Method Based on Unequal Clustering

为了在保证网络节点数据隐私性的同时,提高网络的生命周期,提出了一种轻量级的基于非均匀分簇的安全数据融合方案UCDA。首先根据距离BS节点远近构造不同大小的簇,然后再采用分片重组技术,位于不同簇重叠区域的节点将分片数据发送至不同簇的簇头节点进行数据的混杂,在降低通信开销的同时提高了数据安全性。仿真实验和理论分析证明,UCDA方案在满足一般隐私保护要求的前提下,比SMART算法花费更少的通信开销和计算开销,并保证了数据融合结果的精确性。

In order to ensure the data privacy of the sensor nodes and improve the network life cycle, this paper proposes a low energy-consuming private data aggregation method based on unequal clustering（UCDA）. Firstly,the tentative cluster heads construct clusters of unequal sizes by using uneven competition ranges according to the distance to Base station. Then, the fragment recombination technology is adopted. To reduce the communication overhead and obtain the data privacy, the node in the overlap area of different clusters slice its private data into pieces,and then it send to the cluster heads for mixing in the next process. Simulation results show that UCDA can preserve data privacy, get accurate data aggregation results and cost less communication and computation overhead when compared with the SMART algorithm.