【作者】 许小丰；

【导师】 万江文；

【作者基本信息】 北京邮电大学 ， 机械电子工程， 2010， 博士

【摘要】 无线传感器网络(Wireless Sensor Networks, WSNs)在国家安全、国民经济多方面有广泛的应用前景。安全可靠的数据传输对顺利实现网络功能、延长网络寿命至关重要,是WSNs走向实际应用必须解决的关键问题之一。然而,基于密码体系的安全机制只能抵抗外部攻击,设计思路与实现方法都无法解决网络节点失效或被俘导致的内部攻击问题；另外,可靠的数据传输需要合理的传输控制机制解决网络数据差错和拥塞丢包问题。因此,为了实现网络高效节能、安全可信的数据传输,需要对路由信任评估与传输控制关键技术进行深入研究。研究内容分为三部分：(1)对节点间信任评估与高效路由方法进行研究,在节点信任度量的基础上实现网络路由的高效节能；(2)研究跨层主动式预测数据传输控制方法,解决网络拥塞丢包及数据差错问题,提高网络的整体性能；(3)建立信任评估与传输控制实验平台,对所提算法有效性进行验证。针对传感器节点失效或被俘所导致的网络安全问题,提出了一种基于节点行为策略与改进证据理论结合的信任评估算法。该算法根据节点行为方式制定各种信任因子,基于网络应用场景动态制定各因子系数,进而得到被评估节点的直接与间接信任值；同时,采用模糊集方法,形成证据理论的基本输入向量；在此基础上,计算各间接信任与直接信任值的证据差异,修改D-S证据组合规则,最终合成邻居节点的综合信任值。实验结果表明,新算法解决了网络中恶意节点难以识别的问题,体现了信任值“得到困难、失之容易”的特性,提高了网络的安全性。为了减少节点能耗,提高无线传感器网络生存周期,提出了—种置信区间和禁忌策略相结合的层次型路由算法。该算法根据簇内节点所采数据成高斯分布的特点,使用抽样样本设定置信区间与总量模型进行对比,有效减少了数据发送量；同时为了避免网络出现抽样热点,采用禁忌策略对抽样数据进行禁忌水平线限制。实验结果表明,新算法在满足不同用户准确率要求的前提下,大幅度增加了网络寿命,实现了路由的高效节能。针对数据传输过程中如何选择信任路由的问题,在节点信任评估及路由高效节能研究的基础上,提出了一种无线传感器网络中基于节点信任度量的层次型路由算法。该算法首先采用新提出的信任评估算法对节点进行信任评估,得到各节点信任值；然后结合节点密集度、向心度、信任值大小进行路由主干节点(簇头)信任选举,从而建立节点可信路由表；并利用新提出的层次型路由算法减少簇内能量耗费。在此基础上,根据簇头节点间距离及相关性系数,确定簇头间数据转发关系,进一步减少数据传输能耗。仿真实验表明,该算法实现了传感器网络对路由安全可信、高效节能的要求,解决了网络“感知空洞”和“能耗热点”问题。针对数据传输过程中存在的拥塞丢包及数据差错问题,提出了一种跨层主动式预测数据传输控制协议。该协议根据单节点存储状况及局部网络平均缓存占用量,采用排队论方法,结合局部网络数据量变化趋势,主动预测并调整下一时刻节点发送速率；同时,根据数据包原始优先级、存储等待时间以及邻居节点数量制定MAC层信道竞争策略,动态调整数据发送优先级,保证网络公平性与时效性。实验结果表明,该算法有效保证了网络信息的可靠传输、提高了网络生存周期和可用性,增加了网络带宽的利用率,体现了网络公平性与时效性。为了验证所提算法的有效性,研发了基于无线传感器网络的信任评估与传输控制实验系统。包括自主研发的N201系列传感器节点和网关等硬件设备以及信任评估与控制实验系统的整体架构,研发了节点和网关的NesC程序以及TestBed管理软件。最后,通过实验对信任评估与传输控制性能进行了测试。该实验系统具有通用性和可扩展性,可为信任评估与传输控制算法研究提供验证和测试平台,同时也为无线传感器网络的其他应用研究打下基础。更多还原

【Abstract】 Wireless sensor networks (WSNs) have wide application prospects in terms of national security and all kinds of national economies. It is essential for reliable data transmission to smoothly execute the functions of network and prolong the lifetime of network, which is one of the key issues to be solved for the practical application of WSNs. However, security system based on cryptography can only prevent external attacks, neither design ideas nor implement methods of the system can solve the internal attacks caused by network nodes invalid or compromised. Moreover, it is necessary for reliable data transmission to create a reasonable transmission control method which is aimed to solve packets reliability and losing data packets brought by congestion. Therefore, in order to achieve the trust and reliable data transmission method which is energy efficient in network, it is necessary to make an in-depth research of key technologies of trust routing and transmission control. The research is divided into three parts:(1) The first part researches on the trust evaluation among nodes and the method of efficient routing to achieve the energy efficient network routing based on nodes’trust. (2) The second part researches on cross-layer active predictive data transmission control methods to solve network congestion and data error, as well as improve the overall performance of network. (3) The final part researches on building trust evaluation and transmission control experimental platform to verify the validity of the proposed algorithms.Nodes failure or compromised in wireless sensor networks will lead to serious security problems. In this paper, a node behavioral strategies banding belief theory of the trust evaluation algorithm is proposed. According to nodes’behaviors, a variety of trust factors and coefficients of each factor based network application is established to obtain direct and indirect trust values through calculating weighted average of nodes. Meanwhile, the fuzzy set method is applied to form the basic inputting vectors of evidence theory. On the basis, the evidence difference is calculated between indirect trust values and the direct trust values, which links the revised D-S evidence combination rule to finally synthesize integrated trust value of neighbor nodes. Simulation results have shown that the proposed scheme can effectively solve the network problems which are difficult to identify malicious nodes and represent the characteristic of trust value that’hard to acquire and easy to lose’, further to ensure the security of WSNs.Reducing energy consumption is essential for the life of wireless sensor networks. A confidence interval banding taboo-level of hierarchical routing algorithm for long-lived sensor network is proposed. Using the fact that the intra-cluster data taking on Gaussian distribution characteristics, the new scheme makes sample data setting confidence interval to compare with the total model, which can be effective in reducing the amount of data being sent. In order to avoid hot collected in cluster, taboo method is used for sampling data to calculate the taboo-level. Simulation results have shown that new shecme can satisfy the desired accuracy given by system and lengthen the life of network significantly better than other similar algorithms.As for the issue of how to choose the trust routing during the data transmission, on the basis of nodes’trust evaluation(Chapter 3) and the research of energy efficient routing(Chapter 4), a hierarchical routing algorithm based on nodes’ trust in wireless sensor networks is proposed in this paper. Firstly, the algorithm adopts the new proposed trust evaluation method (Chapter 3) to evaluate and obtain the trust of nodes. Secondly, the trust evaluation algorithm is combined with the density, centrality, and trust of each node to select the backbone of route (cluster head), which is to establish the credibility routing table of each node, at the same time, the new hierarchical routing algorithm(Chapter 4) is used to reduce the internal energy consumption of cluster. Thirdly, according to the distance and related coefficient between cluster heads of network, the proposed scheme determines the data forwarding relationship between cluster heads to further reduce the energy consumption of data transmission. Simulation results have shown that the proposed scheme can achieve the requirements of reliable and energy efficient of network routing, as well as solve the problems of network’perception empty’and ’energy hot spots’.Congestion and data error influence severely the transmission capability and life of wireless sensor networks. A cross-layer active predictive data transmission control protocol for improving network performance is proposed in this paper. According to the cache status of single-node, as well as the average occupancy cache for local network, the proposed scheme adopts queuing theory to analysis data flows, also combined with trends of local network data flow, forecasts and adjusts actively the sending rate of each node at the next time. Whilst, in order to ensure the fairness and timeliness of the network, the protocol has revised competing strategy of MAC according to the original data stream priority, waiting time and still the amount of neighbors, which can adjust dynamically the sending priority of each node. The simulation results have shown that the proposed scheme can effectively ensure the reliable of data transmission. Furthermore, it has outstanding performance in terms of reducing packet loss ratio, transmission delays, the fairness of transmission, as well as power consumption of network.In order to verify the validity of the proposed algorithms, trust evaluation and transmission control experiment system for wireless sensor networks is designed. Firstly, we introduce hardware equipments that are independent developed by our laboratory, including N201 series of sensor nodes and gateways. Secondly, we describe the overall structure of the system and focus on illustrating program designing of nodes and gateways based on the NesC language, as well as the implementation details of TestBed management software. Finally, the performance of trust evaluation and transmission control system is tested by experiments. The system has versatility and expandability, which can not only provide validation and testing platform for the study of trust evaluation and transmission control algorithms, but also lay the basis for other applications and researches of wireless sensor networks.更多还原