基于传感网数据融合路由与隐私保护算法研究

发布时间：2018-04-28 01:36

本文选题：物联网 + 传感网络　；参考：《沈阳建筑大学》2014年硕士论文

【摘要】：物联网(the Internet of Things)是国家信息战略产业中信息产业发展的核心领域,其发展与应用将进一步推进经济社会各个领域信息化进程。物联网应用遍及工农生产业、军事侦查、智能家居、医疗诊断、遥感、智能制造、智能交通、工业自动控制等领域。传感网络是物联网感知物理世界的重要手段,它由大量传感器节点构成。在数据感知的过程当中,网络中会产生海量的冗余数据,采用各个节点直接传输数据到汇聚节点是不可行的,这样不仅严重浪费网络通信带宽和能量资源,还会降低数据的采集高效性和及时性。因此,如何有效利用有限的带宽和能量资源,延长网络的生命周期是无线传感器网络中一个重要研究课题。数据融合技术是解决这一问题的重要方法,通过合并、压缩、计算和评估等手段,有效减少了网络数据传输量,延长网络寿命,提高数据的准确性。然而,传感网络采集数据多为不能外泄的敏感数据,且网内节点多分布在环境恶劣、无人区域等不易控制的环境中。当传感网络采集敏感数据时可能遭受被动攻击(对节点采集敏感数据非法窃听等)和主动攻击(用删除、更改等方法破坏数据的完整性),因此数据隐私保护成为传感网络中亟待解决的问题。本文将数据融合与隐私保护作为主要研究内容,在查阅相关资料、分析研究现状和网络模型的基础上提出了基于能量均衡的分簇路由算法(CRAE)和基于CRAE的隐私保护算法(CPDAA)。CRAE路由算法采用分簇路由算法进行数据传输与融合。在选择簇头节点时不仅考虑剩余能量,还设置最高能量消耗,以避免簇头节点因为能量不足过早死亡,为避免簇头节点由于负载过重使能量消耗过快,选取主簇头和副簇头两个簇头节点,主簇头负责采集、融合数据,副簇头负责传输数据,由于簇形成时会产生极大簇和极小簇,为减少网络的延迟,对极大簇进行二级分簇。CPDAA算法针对CPDA算法进行改进,在完成数据融合的同时保证数据隐私性,防止敏感数据泄露。依据CRAE算法将节点分成不同簇,同一簇内节点依据生成随机数大小划分成不同组,同一组内节点采用CPDA算法对数据加密、解密和融合,并随机选取组头负责转发加密的融合数据至簇头节点。论文采用MatlAB环境对上述算法进行仿真实验,理论分析与仿真实验结果表明CRAE路由算法平衡了各个节点能耗,延长了网络生命周期,有效提高了数据的采集效率；CPDAA算法相比CPDA算法,在确保数据隐私性同时降低了数据通信量。
[Abstract]:The Internet of things (Internet of things) is the core field of the development of information industry in the national information strategy industry. Its development and application will further promote the process of informatization in various fields of economy and society. The Internet of things is widely used in industrial and agricultural production, military reconnaissance, smart home, medical diagnosis, remote sensing, intelligent manufacturing, intelligent transportation, industrial automatic control and other fields. Sensor network is an important means for the Internet of things to perceive the physical world. It is composed of a large number of sensor nodes. In the process of data perception, huge amounts of redundant data will be produced in the network. It is not feasible to transmit data directly from each node to the convergence node, which not only wastes the network communication bandwidth and energy resources seriously. It also reduces the efficiency and timeliness of data collection. Therefore, how to effectively utilize the limited bandwidth and energy resources and prolong the lifetime of wireless sensor networks is an important research topic in wireless sensor networks. Data fusion technology is an important method to solve this problem. By means of merging, compressing, computing and evaluating, it can effectively reduce the amount of network data transmission, prolong the network life and improve the accuracy of data. However, most of the data collected by the sensor network are sensitive data which can not be leaked out, and the nodes in the network are mostly distributed in the environment which is difficult to control, such as the hostile environment and the unattended area. When the sensor network collects sensitive data, it may be subjected to passive attack (illegal eavesdropping on nodes, etc.) and active attack. Therefore, data privacy protection becomes an urgent problem in sensor networks. In this paper, data fusion and privacy protection are the main research contents. Based on the analysis of the current situation and the network model, a cluster routing algorithm based on energy balance and a privacy protection algorithm based on CRAE are proposed. The clustering routing algorithm is used for data transmission and fusion. When selecting cluster head node, not only the residual energy is considered, but also the maximum energy consumption is set to avoid the cluster head node dying too early because of insufficient energy. The main cluster head and the sub-cluster head are selected to collect and fuse the data, and the sub-cluster head is responsible for data transmission. Because of the formation of the cluster will produce a large cluster and very small clusters, in order to reduce the delay of the network, the main cluster head is responsible for collecting, fusion data, and sub-cluster head is responsible for the transmission of data. The two-level clustering. CPDAA algorithm is used to improve the CPDA algorithm to ensure the privacy of the data and prevent the leakage of sensitive data. Nodes are divided into different clusters according to CRAE algorithm. Nodes in the same cluster are divided into different groups according to the size of generated random numbers. The nodes in the same group use CPDA algorithm to encrypt, decrypt and fuse the data. And randomly select the group head to forward the encrypted fusion data to the cluster head node. In this paper, the MatlAB environment is used to simulate the above algorithms. The theoretical analysis and simulation results show that the CRAE routing algorithm balances the energy consumption of each node and prolongs the network life cycle. Compared with CPDA algorithm, CPDAA algorithm can effectively improve the efficiency of data acquisition and reduce the data traffic while ensuring the privacy of the data.
【学位授予单位】：沈阳建筑大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP391.44;TN929.5;TP309

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