基于全网能量均衡的WirelessHART图路由算法

如何均衡使用网络节点能量并生成高可靠路由是WirelessHART网络研究的一个难题,为此提出了一种GRAEB（graph routing algorithm based on energy balancing）图路由算法。首先,网络被初始化为连通的图结构,能够提高丰富的冗余路径。网络管理器根据全网节点剩余能量、通信周期、链路分布等因子生成节点鲁棒系数矩阵,节点通过比较邻居的鲁棒系数来选择最优路径。另外,规定了邻居节点数的上限阈值,每次路由更新只保留鲁棒系数最优的邻居。仿真结果表明GRAEB不仅提高了网络可靠性,而且延长了网络寿命。     

一种鲁棒性强的无线传感器网络位置隐私保护方案

传统无线传感器网络（WSNs）位置隐私保护方案难以解决安全性与网络能耗之间的均衡,为了提高网络隐私信息的安全性,提出一种鲁棒性强的无线传感器网络位置隐私保护方案.首先通过增加伪源节点和伪汇聚节点防止攻击者获得关键节点的位置信息;然后采用伪汇聚节点分组、概率丢弃冗余数据包降低网络资源消耗;最后在Matlab 2012平台下进行仿真对比实验.结果表明：该方案可以提高网络攻击事件检测率,降低网络时延,有效地保护源节点和汇聚节点的位置隐私.     

一种无线传感器网络链式传输分簇路由协议

由于周围环境对无线传感器网络(WSNs)的影响,在布设到特殊环境下时会产生信号的衰减与损耗,导致通信不畅。针对此问题,提出一种以LEACH路由协议为基础适应特殊环境(长直空间)的新型路由算法。本算法采用链式传输,即从内部逐一将信号传输给距空间最外端且距基站位置较近的簇头,克服了内部节点死亡过快的问题。同时簇内采用链式传输并且改进簇头阈值与成簇半径,减小了能量消耗,提高了稳定性,克服了LEACH算法的不足。     

基于最优连通功率控制的WSNs跨层路由优化算法

针对非连通区域节点空洞效应和热点区域节点间通信干扰导致的路由服务质量（QoS）下降问题,提出了一种基于最优连通功率控制的无线传感器网络（WSNs）跨层路由优化算法。算法采用自适应最优连通功率控制策略,在避免路由空洞产生和保证网络连通性条件下,降低热点区域节点数据转发竞争干扰;通过位置信息、剩余能量和干扰等级的跨层信息交互,动态选取最优转发节点,提高网络整体性能。仿真实验表明：算法能够提高路由（QoS）、优化网络生命周期和降低热点区域通信干扰。     

无线传感器网络中多重覆盖算法的研究

在无线传感网器络中的硬件资源普遍受限的情况下,形成优秀的覆盖控制策略己成为无线传感器网络研究领域的热点课题。本文提出了一种能量有效的多重物理覆盖算法,在保障覆盖与连通性的前提下,以能量、覆盖度为衡量指标,采用调度机制实现节点轮换活跃与休眠,有效地提高网络生存时间。仿真实验结果表明,与目前典型算法相比,提出的算法在网络生存时间、能量消耗与消亡节点数上具有显著的优势。     

一种线性时间复杂度的高效路由保护方法

如何高效快速地应对网络中的故障是设计路由协议的基本要求和主要任务。由于动态路由协议在应对网络中的故障时,在协议动态收敛的过程中将会有大量的报文被丢弃。因此,目前路由器厂商普遍采用路由保护方法来克服网络故障,在众多的路由保护方法中,DC（downstream criterion）规则是一种被普遍认可的方法。然而,已有的实现 DC规则算法的时间复杂度普遍较高,并且复杂度随着网络节点平均度的增加而迅速增加。为了应对上述问题,提出一种线性时间复杂度的高效路由保护方案ERPLR（an efficient routing protection method with linear time complexity）,该方法首先提出了备份下一跳计算规则,然后在已有最短路径树的基础上,根据备份下一跳计算规则为所有的源目的节点对计算备份下一跳。在计算备份下一跳的过程中,每个节点和其邻居最多被访问一次,因此ERPLR的时间复杂度为O（V+E）。实验结果表明,与已有的实现DC规则相比较,ERPLR在故障保护率和路径拉伸度两个度量指标结果相似的情况下,在真实网络拓扑和模拟拓扑中,ERPLR分别降低了大约74.93%和78.91%的计算开销,该方法可以极大地降低DC规则的计算开销。     

基于活动区域的移动无线传感器网络路由协议

为了解决移动无线传感器网络中能量效率问题,提出了一种基于活动区域的移动无线传感器网络（WSN）路由协议。本方法使用源和sink节点相对位置来形成路由的活动区域,网络中的移动节点使用睡眠唤醒模式来节约能源。移动向量信息（如当前位置、方向和速度）以及节点的剩余能量,用于选择能够提供最大连接保留时间的邻居,移动向量信息也被用来唤醒活动区域中的移动节点。实验表明,与其他路由协议进行比较,该方法在分组传输过程中具有更高的可靠性。     

Application of statistical mechanics to the analysis of various physical properties of elastomeric networks — a review

This paper examines the application of the statistical mechanics to the analysis of various physical properties of the elastomeric networks. The equilibrium properties of rubber-like networks are discussed, and also some dynamic properties, such as the relaxation spectrum of Gaussian networks. The paper covers a large spectrum of properties of polymer networks such as: fluctuations and chain dimensions in unimodal and bimodal network, effects of entanglements and constraints on the elastic properties of the network, segmental orientation, liquid-crystalline networks, small angle neutron scattering from networks, strain birefringence, elastic properties of filled networks, strain induced crystallization etc. The paper shows that the statistical mechanics can be successfully used to the analysis of almost all physical properties of rubber-like networks.     

Exploring the effect of dry premixing of sand and cement on the mechanical properties of mortar

A spout-fluid bed device was developed for dry premixing sand and cement to produce mortar. The goal of the work was to explore the efficacy of a new method for dispersing cement in sand to produce a mortar with better mechanical and physical properties. This strategy was found to work best at high sand/cement ratios, indicating that the dry premixing is more effective as the cement content is reduced and that it may be possible to produce commercially acceptable mortars with a lower cement content. Other properties of the mortar are also positively affected, including a decrease in the shrinkage and an increase in the workability.     

An immune orthogonal learning particle swarm optimisation algorithm for routing recovery of wireless sensor networks with mobile sink

The growth of mobile handheld devices promotes sink mobility in an increasing number of wireless sensor networks (WSNs) applications. The movement of the sink may lead to the breakage of existing routes of WSNs, thus the routing recovery problem is a critical challenge. In order to maintain the available route from each source node to the sink, we propose an immune orthogonal learning particle swarm optimisation algorithm (IOLPSOA) to provide fast routing recovery from path failure due to the sink movement, and construct the efficient alternative path to repair the route. Due to its efficient bio-heuristic routing recovery mechanism in the algorithm, the orthogonal learning strategy can guide particles to fly on better directions by constructing a much promising and efficient exemplar, and the immune mechanism can maintain the diversity of the particles. We discuss the implementation of the IOLPSOA-based routing protocol and present the performance evaluation through several simulation experiments. The results demonstrate that the IOLPSOA-based protocol outperforms the other three protocols, which can efficiently repair the routing topology changed by the sink movement, reduce the communication overhead and prolong the lifetime of WSNs with mobile sink.