摘要： 传统范围查询方法主要针对一维数据，在感知节点上传的信息较多，导致能耗较高。提出一种基于压缩HMAC算法的两层无线传感器网络多维数据范围查询方法。使用AES对称加密算法生成数据密文及加密索引链，运用反向0-1编码和压缩HMAC算法生成最值比较链，反向0-1编码不需额外进行数值化处理，压缩HMAC算法能够缩短HMAC编码长度，从而减少感知节点的发送数据，降低感知节点的能量消耗。在AliOS Things Developer Kit开发板和iTOP-4412核心板上对该方法进行实验，并从单个周期采集数据个数、感知节点数据位数和采集数据维数3个方面与CSRQ等方法进行能量消耗对比分析，结果表明，该方法能保持数据的完整性，且能量消耗更少。

关键词: 范围查询, 两层无线传感器网络, 隐私保护, 反向0-1编码, 压缩HMAC算法

Abstract: Traditional range query methods are mainly aimed at one-dimensional data, and require more uploaded information at perception nodes, resulting in high energy consumption.Therefore, a multi-dimensional data range query method for two-layer wireless sensor networks is proposed based on the compressed HMAC algorithm.This method employs the AES symmetric encryption algorithm to generate data ciphertext and encryption index chain.Then reverse 0-1 coding and the compressed HMAC algorithm are used to generate the maximum comparison chain.Reverse 0-1 coding does not need additional numerical processing, and the compressed HMAC algorithm effectively shortens the length of HMAC coding, so the sent data of perception nodes is reduced, which decreases the energy consumption of perception nodes.The method is tested on the AliOS Things Developer Kit development board and iTOP-4412 core board, and the energy consumption is compared with the CSRQ method in three aspects:the number of data collected in a single cycle, the number of perceived node data bits and the dimension of collected data.The results show that this method can maintain the integrity of data and reduce the energy consumption.

Key words: range query, two-layer Wireless Sensor Networks(WSN), privacy protection, reverse 0-1 encoding, compressed HMAC algorithm

中图分类号: 

• TP391