OBS网络的拥塞控制汇聚算法分析

传统OBS网络汇聚算法没有综合考虑边缘节点汇聚算法和核心节点的数据调度算法二者之间的相互联系,其通信性能受限。在分析OBS网络边缘节点汇聚算法对核心节点数据调度的影响后,提出了一种新的边缘节点汇聚算法——基于OBS网络的拥塞控制汇聚算法（CCAA）。该算法通过分析边缘节点汇聚参数对数据调度的影响,调整汇聚算法实现对核心节点调度成功率的影响,最终实现了提高核心节点数据调度的成功概率。     

A method for feature contour extraction of triangular meshesbased on multi seed points

An algorithm for extracting feature curves of triangular meshes based on multi seed points is proposed. First, feature contour positions of triangular meshes are detected on the basis of curvature value and normal vector, and these positions are highlighted with difference colours. Then, several seed points on the proper position are assigned and their feature attributes are computed. Next, their node assessment functions are constructed and correct path nodes are chosen. Finally, the curves extracted from the triangular meshes are smoothed. Experimental results show that the method is not only effective to extract closed feature curves and sharp edges, but also useful for opened feature curves and the region that the features change gently. It has higher accuracy than other methods to detect feature at the branch feature regions.     

Distribution of trust model in P2P network based on equilibrium theory

There are a large number of malicious attack nodes and collusion groups in P2P(peer to peer) network, and the existing trust models improve the P2P network environment to some extent, but the emphasis of the models are different, which are unable to fully solve large-scale malicious attacks and deception. Therefore, a P2P trust model based on equilibrium theory is presented. The model consists of the construction of the trust structure, the malicious node detection and trust speculation. It constructs trust network according to the equilibrium theory, uses the equilibrium theory to define nodes balance factor, detects balance malicious nodes by calculating the impact of malicious behavior on the network, and adopts trust inference algorithm to estimate trust nodes to prevent distrust network nodes being added. Experimental results show that the model is reliable, and the algorithm is efficient and robust.     

Analysis on the optimum dynamic quality of wireless mesh network

In order to procure the optimum quality of control for full-controlled wireless mesh network, the primary influencing factor network time delay is analyzed. In order to get the optimum quality of control,the minimum network time delay should be acquired,and the algorithm of branch and bound is given to solve this problem. According to the numerical simulation, the quality of control for the whole network system with decreasing the delay time can be optimized by adjusting the number of nodes, the average transmission hop counts, and the probability of successful channel access and transmission for random nodes.     

Repeated game theory intrusion detection model for the Internet of Things

The existing security methods cannot be applied to the Internet of Things due to the defects of communication nodes. To solve this problem, an intrusion detection model based on repeated game theory is presented. A repeated game model algorithm for detecting malicious nodes is built, and the algorithm of Quantal Response Equilibrium (QRE) is used for optimizing the model and making results reach the Nash equilibrium. Moreover, a common punishment strategy is introduced to improve the success of transfer data in this model. The results of the simulation represent that this model can restrain malicious nodes attacking effectively and improve the efficiency of network.     

DHT的分层结构多出口选择问题研究

为了提高系统可靠性和查询效率,提出了具有多管理节点（出口节点）的DHT分层模型,并给出了3种查询算法：最短路径选择算法、基于热土豆模型的最小化组内流量算法和出口节点负载均衡选择算法。通过仿真实验对3种算法在查询效率、流量分析和负载均衡3个维度进行了分析比较,基于热土豆模型的最小化组内流量算法具有最高的查询效率,但是负载均衡性能最差,出口节点负载均衡选择算法具有最好的负载平衡性,但查询效率最低,最短路径算法性能则介于上述两种算法之间。同时对传统分层结构所采用的随机查询算法与基于热土豆模型的最小化组内流量和最短路径查询算法进行了性能对比。     

Study on Computer 3D-Reconstruction Algorithm of the Contour Points Matching Interpolation for Serial Cross Images

A computer 3D-reconstruction algorithm was proposed for serial cross images,which is called contour points matching interpolation algorithm. The intermediate contours betweentwo neighbouring contours are preduced by contour points matching interpolation to form 3D-shapeof the reconstructed object. This algorithm is simple and can be easily implemented. Its advantagesare fast speed and strong adaptability for medical serial cross images 3D-reconstruction. Experi-ments show that the results are satisfactory.     

Preprocessor of Reinforced Concrete FEM Analysis

Reinforcing element and concrete element have effects on the order of the stiff-matrix of the reinforce-concrete FEM. The program divided the elements is programmed by FORTRAN language in current analysis, and the data of the elements are stored by the array. The stiff-matrix of the reinforce-concrete FEM is extended by the large residual between the serial numbers of the nodes of cohering element. This paper establishes the graph class, path class and point class via objectoriented programming. The storage of the points and the paths by the chain structure realization of copying graph, moving graph, adding graph, continuously numbering the cohering elements are built. This paper presents the example of the dividing domain with the crack.     

An improved localization algorithm based on RSSI for landslide monitoring

In order to overcome the existing problems of low automation, high cost and difficult to implement in the area of landslide monitoring, this paper presents a new method of RSSI (Received Signal Strength Indicator)based positioning technology without any one-off instruments to monitor landslide surface displacement. By adding weighted factors, the improved positioning algorithm can estimate the parameters of the path loss model dynamically and calculates the communication distance of network nodes in real-time, which can improve positioning precision and reduce the impact of environmental changes on it. The MATLAB experiments show that, compared with the traditional RSSI based localization algorithm using fixed pass loss model, the improved algorithm could significantly reduce the average error.     

Hierarchical self-localization of underwater wireless sensor network nodes

The follow-up application of underwater wireless sensor network is influenced by accuracy of self-localization of nodes. The self-localization of nodes is discussed in this paper. First of all, nodes of underwater wireless sensor network are classified into several levels according to the accuracy of position of nodes and the levels are from the first to the fifth in accordance with accuracy of nodes from high to low respectively. Secondly, the level of anchor nodes can be known by those unknown nodes from the information given by the anchor nodes themselves, At the same time the unknown nodes are able to be located in the area controlled by the first level of anchor nodes that are as the aggregation. Then the positioning algorithm is designed correspondingly in accordance with the accuracy level of nodes. Finally, the positioning algorithm is simulated and analyzed. The result shows that the unknown nodes can be located effectively by hierarchical control.     

一种基于距离和角度的无线传感器网络GPSR协议

传感器节点能量是影响无线传感器网络的生存周期的关键因素,基本的GPSR协议所使用的贪婪算法忽略了角度因素对下一跳选择的影响,在转发失败遇到空洞问题时只能进行周边边界转发算法,以损耗节点能量为代价。为了节约节点能量,延长网络生存周期,从改进GPSR协议出发,综合考虑距离和角度这两个因素解决路由过程中的空洞问题。仿真实验表明,改进后的协议是网络节点消耗大大减少,网络生存时间为300 s,长于基本GPSR协议下的200 s。该协议缩短了路径长度,节约节点能量,减少能量的消耗,延长了网络生存时间。     

Corner detection based on evolution difference of plannar curves in B spline scale space

In order to improve image corner detection precision and efficiency, a novel corner detection algorithm based on B spline scale space evolution difference is proposed. The norm of DoB is defined as corner response function to evaluate the multi scale evolution difference. The DoB corner detector confluents the image boundary features with different scales, which can not only strengthen the response of the feature points, but also depress the influence of noise. Among all corner detection algorithms based on B Spline, the proposed algorithm is relatively lower for computation complexity and faster. The comparative experiments demonstrate that the proposed algorithm works well for localization, robustness against noise, as well as invariance to rotation and scalability.     

Design fuzzy membership functions based on the posterior probability weighting

The determination of fuzzy membership function in the fuzzy support vector machine (FSVM) is a difficult problem. To solve the problem of being sensitive to the noises and outliers in support vector machine, by the inspiration of Bayesian decision theory, combining with sample density characteristics, sample points relation between same class and other class is researched, and the tightness on each sample points is described. Based on that, method of posterior probability and sample density weight are given to each sample, and new fuzzy membership function is proposed. The detection of the noises and outliers is avoided by this method. Numerical simulation shows that the improved fuzzy membership function method is effective.     

标记辅助选择育种中QTL基因型的多点联合推断

传统的育种方法对数量性状的选择存在很大难度,现代分子标记技术为实现控制数量性状基因的准确选择提供了有效的技术手段。目前分子标记辅助选择实践仅是对标记基因型的选择,而非直接对QTL基因型进行选择。尽管标记基因型容易获得,但标记基因型通常并非QTL基因型,除非有关的QTL恰巧在标记座位。因此,如何鉴别QTL的基因型成为分子标记辅助选择的关键。QTL基因型通常需要通过分子标记基因型进行推断,由于标记信息的不完全或缺失,使得对个体QTL基因型的鉴别会发生困难。本文在四向杂交设计的基础上,结合贝叶斯理论和马尔可夫链原理,提出一种通用的QTL基因型多点联合推断方法,该方法能够很方便地处理显性标记和缺失标记,同时结合标记信息和表型数据联合推断QTL基因型的条件概率。模拟研究发现,表型数据选择的效果较差,其选择的个体QTL基因型基本上都是错误的,而应用本文所论述的方法,将表型数据与标记数据相结合选择,对QTL基因型的判断正确,且推断的把握性很高。     

Adaptive relay selection algorithm in decode-and-forward cooperative communication networks

An adaptive relay selection algorithm(ARS) is proposed to optimize the performance of decode-and-forward cooperative communication networks, both system outage probability and average numbers of cooperative relays are analyzed. When the direct transmission between source and destination is fail, according to the channel quality, the destination orders relay nodes in the decode set, and the ordered relays are included in cooperation in turn until the instantaneous received SNR at destination is not smaller than the preset SNR threshold. Simulation results show that, the proposed algorithm can get optimal outage performance, decrease the average numbers of cooperative relays efficiently, to incrense bandwidth efficiency and reduce system overhead.     

Restoration algorithm with wavelength reservation collision avoidance in ASON

Aiming at the problem of link fault restoration in ASON, an improved equalizing routing algorithm (ERA) is introduced to proportion the load at the routing phase. In order to solve the easy blocking problem for the network without wavelength converter because of the wavelength continuity constraint, the algorithm WRCA is proposed at the wavelength assignment phase. This algorithm is realized by adding collision detection object (CDO) in the path message of the resource reservation protocol with traffic engineering extension (RSVP TE). Depending on the value of the CD flag, different wavelength selection strategies are applied at the destination node, and the blocks resulting from wavelength reservation collision are reduced. The simulation experiments compare four wavelength assignment algorithms with the same routing algorithm ERA. The results show that compared with the traditional first fit algorithm (FF) and random fit algorithm (RD), the FF and RD employing CD scheme can effectively reduce the blocking ratio of the whole network, and enhance the practical applicability of the restoration algorithms.     

遗传算法的DV-Hop算法改进

DV-Hop算法中,平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差,对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离;然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离,减少平均每跳距离带来的误差。仿真结果表明,在不增加硬件开销的基础上,改进算法能够有效提高算法的定位精度,并且具有较好的稳定性。     

Improvement and performances of DV hop localization algorithm in wireless sensor networks

In order to improve the node localization precision of Range Free based DV Hop localization algorithm in wireless sensor networks (WSNs) with randomly distributed nodes and dynamic topology, the improved algorithm is proposed. After analyzing the DV Hop algorithm, considering the obvious errors of the estimated node coordinates calculated by Polygon based method in traditional DV Hop algorithm, the numerical iterative algorithm is constructed by employing Taylor series expansion, and simulation studies for the improved DV Hop algorithm are conducted. The selection criteria for the convergent threshold of iterative step is determined, the localization performance of the improved localization algorithm is analyzed by comparing with the traditional DV Hop algorithm under the same condition of selected convergent threshold and simulation parameters, while the calculation amount and convergence rate of the improved algorithm are also measured by the statistic iterations. The simulation results show that by selecting reasonable iterative threshold values and appropriately increasing calculation amount for node localization, the improved DV Hop localization algorithm greatly improves the localization precision and the error stability, which is feasible for node localization in WSNs with both randomly distributed nodes and dynamic topology.     

An improved HEED clustering algorithm for Wireless Sensor Network

In wireless sensor network, routing protocols which based on clustering have the advantages of energy consumption, topology management and data fusion. The HEED protocol, which generates cluster heads based on distributed algorithm, drives up the rate of clustering and creates well distributed cluster heads. However, it does not consider the mobility of nodes in the network. When the distance between neighbor nodes has changed, the AMRP method which decides the node belongs to different cluster heads would cause problems such as high energy consumption, short lifetime of network and so on. Responding to these problems, the paper proposes the S HEED, a clustering algorithm based on stability, which chooses the stability as a parameter of nodes when choosing a cluster head. With S HEED algorithm, the high energy consumption problem among cluster nodes and cluster heads caused by the mobility is tackled. The simulation experiment demonstrates that the S HEED algorithm lower the energy consumption of cluster heads and prolongs the network lifetime.     

An improved morphological edge detection algorithm of medical image

Medical images usually contain much noise which affects the edge detection accuracy. Focusing on this problem, based on the edge detection operator in mathematical morphology, an improved edge detection algorithm is presented by combining the features of the multi structure elements and the multi scale edge detection algorithm. The algorithm performs opening and closing operations on the data with the alternative sequence filters and the structure elements. The weighting operation is applied with different weight coefficients for horizontal, vertical and diagonal directions, while the edge detection operator with dilation type is calculated to obtain the improved edge detection algorithm. The steps of the algorithm are described. The algorithm is used to extract the edge of MRI image as well as the image of Lena. The experimental results indicate the algorithm can considerably improve the edge resolution of the traditional morphological edge detection methods and is practical.