基于Slepian-Wolf理论的无线传感器网络分簇算法及改进

发布时间：2018-01-14 00:32

本文关键词：基于Slepian-Wolf理论的无线传感器网络分簇算法及改进　出处：《大连理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：无线传感器网络利用微型传感器与网络技术相结合,打破了人们对物理世界信息获取方式的传统观念,成为21世纪的一种新兴技术。无线传感器网络不仅在各项科研工作中产生了很大的影响,而且在社会实践中也有着广泛的应用。通常,在无线传感器网络中,节点的资源是十分有限的,特别是能量资源。地理位置靠近的节点通常具有一定的相似特性,称为时空相关性,这样就导致了冗余数据的产生。传输这些冗余数据不仅消耗了大量资源,而且降低了对有效数据的感知。在这种条件下,如何合理分配资源,提高网络的能量效率,从而延长网络的寿命,已经成为研究人员关注的热点。为了解决上述问题,本文对分簇式路由协议(即分簇算法)进行研究与设计,主要工作如下：首先,本文对无线传感器网络中的路由技术和分簇算法进行了概述,给出了一些经典分簇算法的描述,同时,介绍了本文中涉及的相关理论基础。为了解决无线传感器网络中存在的数据相关性问题,本文提出了一种基于Slepian-Wolf理论的局部数据相关性感知分簇算法LDCA。该算法综合考虑了数据的时空相关性、通信距离、剩余能量等重要因素,定义了平均熵和节点连接度作为选择簇首的决定条件,并且设计了有效的分布式算法来获得更好的网络性能和能量效率。仿真结果表明,LDCA分簇算法不仅能够获得较好的分簇结果,而且有效的降低了通信数据量。此外,在能量均衡方面也优于其它算法。其次,为了避免分簇算法在更新过程中额外的能量开销和时间开销,并且提高网络数据传输的可靠性,本文针对LDCA算法中的不足,进行了相应的改进,并提出了一种使用随机更新策略的能量高效分簇算法EECRU。在簇的更新算法中,本文使用了随机更新策略和簇首轮转机制相结合,解决了传统算法中存在的不足；在数据传输过程中,采用节点采样率控制方法,使传感节点对数据的感知更加智能,提高海量信息处理效率。同时,提出了分簇更新理论,来说明随机更新算法的高效性,并给出了数学证明。本文在相同的网络条件下,对EECRU、LEACH、DDCD三种算法分别进行了仿真实验。对比结果表明,EECRU提高了网络能量效率,能够保证网络数据可靠传输。最后,对全文进行了总结,并提出了下一步工作的重点以及对未来的展望。
[Abstract]:Wireless sensor network using micro sensor and network technology, breaking the traditional concept of people to obtain information of the physical world, become a kind of new technology in twenty-first Century. Wireless sensor networks not only have great influence on the research work, but also in social practice has been widely used. Usually, in wireless in Sensor Networks, the node resources are very limited, especially energy resources. The node location near usually has the same characteristics, known as spatial and temporal correlation, this leads to redundant data generation. These redundant data transmission not only consumes a lot of resources, but also reduces the data in perception. Under this condition, how rational allocation of resources, improve the energy efficiency of the network, so as to prolong the lifetime of the network, has become the focus of attention of researchers to understand. To solve these problems, this paper on the cluster based routing protocol (i.e. clustering algorithm) for research and design, the main work is as follows: firstly, this paper summarizes the routing technology in wireless sensor networks and clustering algorithm, some classical clustering algorithms are described, meanwhile, introduces the related theories of this article. In order to solve the problem of data correlation in wireless sensor networks, this paper proposes a local data based on Slepian-Wolf theory related to the perception of clustering algorithm LDCA. the algorithm considering the temporal correlation, data communication distance, residual energy and other important factors, the definition of average entropy and node connectivity as cluster head selection the decision condition, and the design of the distributed algorithm is effective to obtain network performance and energy efficiency better. The simulation results show that the LDCA algorithm can not only get a Good clustering results, and reduce the amount of communication data. In addition, the energy balance is better than the other algorithms. Secondly, in order to avoid the overhead of clustering algorithm for energy cost and additional time during the update process, and improve the reliability of data transmission network, aiming at the shortage of LDCA algorithm, the corresponding the improvement, and proposes a random update strategy of energy efficient clustering algorithm in EECRU. cluster update algorithm, this paper uses random update strategy and cluster head transfer system of combining, solves the problems existing in the traditional algorithm; in the data transmission process, methods used to control the sampling rate of the node. On the perception of data more intelligent sensor node, improve the efficiency of massive information processing. At the same time, put forward the cluster renewal theory to illustrate the efficiency of the random update algorithm, and gives the mathematical proof in this paper. The same network conditions of EECRU, LEACH, DDCD three kinds of algorithms are simulated. The comparison results show that EECRU improves the energy efficiency of the network, can guarantee the reliable transmission of network data. Finally, a summary of the full text, and put forward the focus of the next step and the outlook for the future.

【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN929.5;TP212.9

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