Sink placement on a 3D terrain for border surveillance in wireless sensor networks

With their distributed nature and redundant operation capability, wireless sensor networks are very suitable for border surveillance scenarios that track intruders trying to breach to a safe side. In such scenarios, keeping the operation going on for as long as possible is the most important aspect of the network. We propose that by placing sink at a carefully selected coordinate will results in a longer living network. We also place restrictions on the candidate locations so that the sensing quality of the network is above a useful predetermined value and the sink is placed in a relatively safe location to avoid destruction. In order to find the suitable coordinates we propose a modified lifetime metric which takes quality and safety measures into account. We also propose a genetic algorithm which uses a discrete event simulator-in-the-loop over a three dimensional terrain to find locations for the sink that fits the given quality and safety restrictions. Using a three dimensional underlying terrain makes the proposed approach more realistic. The results obtained for various sensor network scenarios indicate that the proposed algorithm can find locations that increase the lifetime by also considering the sensing quality and safety.     

RBC-OLSR: Reputation-based clustering OLSR protocol for wireless ad hoc networks

We consider the problem of assuring the trustworthiness (i.e. reliability and robustness) and prolonging the lifetime of wireless ad hoc networks, using the OLSR routing protocol, in the presence of selfish nodes. Assuring the trustworthiness of these networks can be achieved by selecting the most trusted paths, while prolonging the lifetime can be achieved by (1) reducing the number of relay nodes (MPR) propagating the topology control (TC) messages and (2) considering the residual energy levels of these relay nodes in the selection process. In this paper, we propose a novel clustering algorithm and a relay node selection algorithm based on the residual energy level and connectivity index of the nodes. This hybrid model is referred to as H-OLSR. The OLSR messages are adapted to handle the cluster heads election and the MPR nodes selection algorithms. These algorithms are designed to cope with selfish nodes that are getting benefits from others without cooperating with them. Hence, we propose an incentive compatible mechanism that motivates nodes to behave truthfully during the selection and election processes. Incentive retributions increase the reputation of the nodes. Since network services are granted according to nodes’ accumulated reputation, the nodes should cooperate. Finally, based on nodes’ reputation, the most trusted forwarding paths are determined. This reputation-based hybrid model is referred to as RH-OLSR. Simulation results show that the novel H-OLSR model based on energy and connectivity can efficiently prolong the network lifetime, while the RH-OLSR model improves the trustworthiness of the network through the selection of the most trusted paths based on nodes’ reputations. These are the two different processes used to define the reputation-based clustering OLSR (RBC-OLSR) routing protocol.     

基于ROI运动区域的分布式视频编码方法

传统的分布式视频编码方法中,视频帧的解码通常采用内插或外推的方法,然而对于运动剧烈视频帧的解码效果却并不理想,会产生重影、鬼脸等现象.因此,提出了一种基于ROI运动区域的分布式视频编码解决方案,通过在编码端提取ROI辅助信息,然后在解码端将其与边信息做融合处理来得到更加准确的边信息,从而提高视频解码的质量.实验结果表明,与传统的分布式视频编码方法相比,基于ROI运动区域的分布式视频编码解决方案在性能上平均有3.1db的提高.     

基于FPOMDP的无线传感器网络动态调度算法

针对无线传感器网络节点能量有限、数据采集易受环境影响的问题,提出一种基于可分解部分可观察Markov决策过程FPOMDP( Factored Partially Observable Markov Decision Process )的节点休眠调度算法.通过节点空时相关模型求取休眠节点数据,利用网络数据准确性和节点能量间的条件独立关系,构造状态转移函数、观察函数和奖赏函数,采用值迭代求解算法求取最优策略,实现节点动态调度.仿真结果表明,该算法能够在保证数据准确性的前提下,有效降低节点能量消耗,延长网络生存时间.     

自主式水下航行器三维路径跟踪的神经网络H∞鲁棒自适应控制方法

本文研究了存在模型不确定以及外界未知扰动情况下的自主式水下航行器(AUV)的三维路径跟踪控制问题. 针对此问题, 首先利用时标分离原理及正交投影Serret-Frenet坐标系建立了描述AUV质心运动及姿态运动的的仿射非线性数学模型. 其次, 在控制器设计中运用神经网络H∞鲁棒自适应算法克服了模型的不确定性及扰动, 同时在控制器设计中利用了主导输入的思想, 降低了闭环系统的复杂度, 减少了实时计算工作量, 便于工程应用. 基于Lyapunov理论的分析保证了系统的稳定性. 仿真结果表明, 路径跟踪控制律可以保证AUV沿期望路径运动, 并且具有良好的动态性能.     

时滞反应扩散Hopfield神经网络的滑动模控制

研究了一类具有S--分布时滞和反应扩散项的Hopfield神经网络的滑动模控制问题. 首先改进了一类Hanalay不等式, 给出了一种范数不等式. 然后通过等效控制方法建立了系统的滑动模态方程, 并利用不等式技巧分析了它的吸引集的存在性和零点的指数稳定性. 在此基础上设计了变结构控制器, 给出了运动轨线到达滑动模态区的时间估计. 最后给出了一个例子验证了本文的结果, 并利用MATLAB作出了仿真.     

发动机试车数据拟合算法的研究与实现

针对发动机虚拟测试系统的需要,对某型号发动机试车的14个测试参数采用最小二乘方法结合BP神经网络进行数据拟合。根据测试数据的特点进行分类研究。试验验证表明,所采用的方法结果准确,满足发动机虚拟测试系统的要求。     

12 m跨超声速风洞运行监测系统研究

为改善风洞试验条件和提高试验效率,针对1.2m跨超声速风洞进行了运行监测系统研究.针对风洞环境复杂、监测对象分散的特点,引入无线传感器网络构建了基于多传感器的分布式风洞运行监测平台.重点研究了基于BP神经网络的无线传感器网络数据融合和基于D-S证据理论的多传感器信息融合在风洞运行监测中应用.在实际应用中取得了良好的效果.     

无线传感器网络信息时空融合模型与算法研究

信息融合是解决无线传感器网络能量和通信带宽受限的有效途径,提出了一种无线传感器网络信息时间和空间多级混合融合的结构模型。首先对距离汇聚节点较远的节点信息进行时间融合和对距离汇聚节点较近的节点信息在汇聚节点进行时空融合,然后在汇聚节点对两种节点的融合结果进行全网络的空间融合。就该模型提出了基于DS证据理论的多级时空融合算法。数据分析结果表明:该模型能够降低节点能耗,延长网络寿命。     

航空自组网贪婪地理路由协议研究

在全面总结航空自组网路由协议研究现状的基础上,针对大尺度、高动态的航空通信环境,仿真评估了贪婪地理路由协议GPSR的适用性。仿真结果表明,当飞行器低速运动时,GPSR协议能够较好地适应航空自组网环境,性能优于AODV协议,然而当飞行器运动速率增大后,GPSR协议性能下降,难以满足高动态航空通信的需求,必须对协议中周期性HELLO发送机制、贪婪转发策略等方面进行改进。