面向传感器网络大数据传输应用的数据压缩与传输优化算法的研究与应用

发布时间：2018-01-16 05:14

  本文关键词：面向传感器网络大数据传输应用的数据压缩与传输优化算法的研究与应用　出处：《电子科技大学》2014年硕士论文　论文类型：学位论文

  更多相关文章： 无线传感器网络 相似性分簇 最小传输代价 分簇数据压缩

【摘要】：无线传感器网络(Wireless Sensor Networks,WSNs)是由大量节点自组织而成,集信息采集、处理和传输为一体的网络,被广泛应用于环境监测、栖息地监控和地震探测等诸多领域。WSNs中节点的能量是有限的,而数据传输占用了大部分能耗。因此,如何减少网络数据传输能耗成为了WSNs的关键问题。本文在研究了WSNs中分簇路由协议和数据压缩两种节约数据传输能耗技术的基础上,结合WSNs环境分布中呈现的区域特性,提出了基于节点相似性的分簇算法(Sensor Similarity-based Clustering,SSC)和基于最小传输代价的路由算法(Minimum Transmission Cost-based Routing,MTCR),并结合这两者设计了基于节点相似性的分簇压缩传输方案(SSC-based Data Compression and Transmission,SSCDCT)。本文的主要工作如下:1)提出了基于节点相似性的分簇算法(SSC)。通过对WSNs工作环境的区域性进行研究,提出了节点相似性的度量模型,并依据该模型提出了SSC算法。SSC算法将区域内的相似节点划分到同一个簇中,使得簇内节点具有较高的相似性,从而利于数据的压缩工作。压缩算法能挖掘和消除更多数据中的冗余,减少数据的传输量。2)提出了基于最小传输代价的路由算法(MTCR)。通过分析现有分簇协议在簇内、簇间数据路由方式在大规模传感器网络中的不足,结合传感器节点的能量消耗模型,提出了MTCR。MTCR通过控制簇首覆盖范围和节点度大小实现网络中单跳与多跳的混合路由方式,最大限度地节约网络传输能耗和平衡节点的能量消耗。3)提出了基于节点相似性分簇的压缩方案(SSCDCT)。SSCDCT利用SSC将相似节点的聚集起来,并用压缩算法对它们的数据进行压缩,然后利用MTCR路由协议传输压缩后的数据。SSCDCT将WSNs数据压缩传输分为了三层,层次之间相互协作,以实现最大限度地减少数据传输量和网络的传输能耗,实现延长网络生存寿命的目的。实验和案例研究表明,相对LEACH等分簇协议而言,SSC使簇内节点的平均幅度相似性提高了15%左右,趋势相似性提升了8%左右;MTCR相比LEACH,LEACH-C首节点死亡FND时间延迟了至少14.3%以上,半数节点死亡HND时间延迟了25.5%以上;SSCDCT相比使用LEACH-C的分簇压缩网络,其FND时间延迟了12.1%以上,HND时间延迟了14.5%以上。
[Abstract]:Wireless Sensor Networks (WSNs) is a network composed of a large number of nodes, which collect, process and transmit information. It is widely used in many fields, such as environmental monitoring, habitat monitoring and seismic detection. The energy of nodes in WSNs is limited, and data transmission takes up most of the energy consumption. How to reduce the energy consumption of network data transmission has become the key problem of WSNs. In this paper, we study the clustering routing protocol and data compression in WSNs to reduce the energy consumption of data transmission. Considering the regional characteristics of WSNs environment distribution, a clustering algorithm based on node similarity is proposed, which is called Sensor Similarity-based Clustering. SSCs and the minimum Transmission Cost-based routing algorithm (MTCRs). Combining these two schemes, a cluster compression transmission scheme based on node similarity is designed, which is based on SSC-based Data Compression and Transmission. The main work of this paper is as follows: 1) A clustering algorithm based on node similarity is proposed. The region of WSNs working environment is studied. According to this model, the SSC algorithm is proposed to divide the similar nodes in the region into the same cluster, which makes the nodes in the cluster have high similarity. The compression algorithm can mine and eliminate the redundancy of more data. To reduce the amount of data transmission. (2) A routing algorithm based on minimum transmission cost is proposed. By analyzing the existing clustering protocols in the cluster, the data routing between clusters in large-scale sensor networks is insufficient. Combined with the energy consumption model of sensor nodes, a hybrid routing scheme of single-hop and multi-hop is proposed by MTCR.MTCR, which controls the coverage of cluster heads and the size of nodes. In this paper, we propose a compression scheme based on node similarity clustering (SSCDCT). SSCDCT uses SSC to aggregate similar nodes. The compression algorithm is used to compress their data, and then the compressed data is transmitted by MTCR routing protocol. The compressed data is divided into three layers, which cooperate with each other. In order to minimize the amount of data transmission and network transmission energy consumption, to achieve the purpose of prolonging the network lifetime. Experiments and case studies show that compared to the LEACH equal clustering protocol. SSC increased the average amplitude similarity of cluster nodes by about 15%, and increased the trend similarity by about 8%. Compared with LEACH-C, MTCR delayed the FND time of the first node of LEACH-C by more than 14.3%, and the HND time of half of the nodes was delayed by more than 25.5%. Compared with the clustering compression network using LEACH-C, the FND time of SSCDCT is delayed by more than 12.1% and more than 14.5%.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN929.5
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本文编号：1431689