Trust management scheme based on community model for mobile Ad hoc networks

The security issues in mobile Ad hoc network, especially caused by inner malicious nodes are analyzed. By tracking the behavior of nodes, trust level of each node can be evaluated and managed; then actions of malicious nodes will be constrained and the security and reliability of entire network are enhanced. According to the features of Ad hoc. The scheme proposed in not only extends the conception of trust but also include the trust computation model and trust management mechanism. Simulation experiments show the novel scheme is more efficient than other trust schemes in traditional protocols.     

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.     

Compensation trust evaluation model of grid service

It is difficult to distinguish the cheating and other malicious behaviours in the grid service trust evaluation. A trust evaluation model for grid service based on compensation is proposed.With market mechanism, service provider and demander present the expected profit and compensate price for their behaviours to maximize their own profit. The game theory is applied to balance the expected profit and compensate price. Based on the game theory, evaluation trade strategy achieves perfect Bayesian equilibrium. Service provider and demander can choose their own trade strategy to maximize profit. Theoretical analysis and simulation results show that the service demanders can abandon the cheating motivation voluntarily, while the service providers can make right decision to choose trust evaluation. Compared with the existing model, the precision and security of the trust evaluation is enhanced greatly, while the calculating and communication cost is reduced remarkably.     

Mechanism of Resource Discovery Based on Trust Network

How to effectively locate resources is a very important factor affecting the performance of Grid environment.The authors propose a novel method which utilizes trust relations existed implicitly among network nodes to construct a secure and available resource trust network(SARTN),meanwhile provide the theory and method of SARTN.Combining passively discovery with actively discovery,applying Small World theory,optimized time complexity is achieved, and the performance of Grid resource discovery is promoted.Through analysis,the proposed solution is scalable,secure and efficient in Grid.     

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.     

日光温室小气候预报技术研究

为了提高设施农业气象服务水平,促进中国设施农业发展,通过对日光温室内外气象条件对比观测,分别采用BP神经网络、逐步回归和能量平衡原理构建了温室内气温预报模型,探讨能适用于业务服务的小气候预报技术方法。结果表明,基于BP神经网络的预报模型虽预报精度高,由于种植作物生长特性差异较大,缺乏服务的广适性;通过能量平衡原理构建的预报模型机理性强,但相关参数难以获得,预报精度差,服务时效短;采用逐步回归方法构建的温室温度预报模型较前两者具有比较优势,且预报时效可以为未来的1~7天,比较适合于目前气象部门开展设施农业气象服务。     

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.     

An Unicast Fault-tolerant Routing Algorithm on Locally Twisted Cubes

The locally twisted cube is a newly topological structure of network. The authors we design a unicast fault-tolerant routing algorithm on the locally twisted cube by utilizing safety levels and the feature of the network. The performance of the proposed algorithm is evaluated through simulation experiments. When the number of faulty nodes reaches or exceeds half of the total, it can still achieve a quite high percentage of successful routing. An additional advantage of the routing algorithm is that it is highly probable that the selected route be a shortest route between the associated nodes.     

Improvement and Application on Back Propagation Network Based on Partial Least-squares Algorithm

This paper proposes a novel BP network model based on nonlinear iterative partial least-squares algorithm which can fit nonlinear data. The novel BP network model can reduce iterative step number and advance learning effieieney. This paper pretreats data by nonlinear iterative partial least-squares algorithms. The weights initialization of input floor and output floor are set by applying the loading weights of dependent variable and cause variable, the member of hidden nodes are set by applying factor numbers of nonlinear iterative partial leastsquares algorithm, the connection co- efficient is set by applying the connection matrix B. Performances of the BP, PLS, and PLS-BP are analyzed and compared. The results show that the PLS-BP has better fitting and forecasting than BP and PLS.     

The Multi-objective Fuzzy Optimal Power Flow Model and its Neural Network Algorithm

This paper has presented a multi-objective fuzzy optimal power flow medel.Inthe model , the multiple objectives, such as the minimum generation cost and the minimum powerloss, have been considered simultaneously, A new algorithm based on neural network models is aisopresented,in which the neural networks are employed to express, the membership function of fuzzysets and solve the optimization problems. The validity of model and algorithm is verified with numerical examples.     

AUTOMATIC CONTINGENCY SELECTION AND RANKING USING AN UNIFIED MODEL AND ALGORITHM FOR P - AND Q - SUBPROBLEM

A new approach of the automatic contingency selection and ranking with the network flow programming (NFP) is presented in this paper. NFP is adaptable to change the network topology as the transmission or generation branches arc in single or multiple outage. Thus the fast calculation of the contingency states by NFP cm provide the urgent information in real time N- 1 security analysis. In the paper, automatic contingency selection and ranking forP- and Q-type subproblem arc solved by an unified network flow model and algorithm. It is based on the existence of weak coupling between real and reactive quantities in power systems. The performance indices to assess the severity of contingencies are defined as the total real and reactive load required to be curtailed. The proposed ACS technique including the model and its algorithm are examined with IEEE 5-, 14-, 30-, 57- and 118- bus test systems on M-340. And the encouraging results are given in the paper.     

AUTOMATIC CONTINGENCY SELECTION AND RANKING BY NETWORK PROGRAMMING APPROACH

This paper presents a new approach ,to the automatic contingency selection and ranking by the network flow programming (NFP). A complex cost optimisation model based on economy and security, and several simplified models are proposed in the paper. The performance index is the total load curtailment or its weighted value. All the solution algorithms are OKA. The model and its algorithm is tested on IEEE 30-Bus System and the encouraging results are obtained.     

Investigations of Distribution System Planning of Loop Configurations Using a Genetic Algorithm

The distribution system planning is performed with a loop configuration constraint from scratch.With Evolutionary Algorithm,a sample distribution network is designed with a loop configuration,in which the system is operated as radial configuration.It firstly introduces the mathematical model for distribution network planning,then the application of Evolutionary Algorithm for the planning of distribution network.By using the theory mentioned above, Visual C++ is applied to develop the distribution network optimization software.Finally with the optimization process of 17 nodes system being showed,the presented algorithm's utility and validity is verified.     

Research on immunization strategies based on independent sets of complex networks

According to the concept of independent set, this paper proposes a new immunization strategy of complex networks which immunizes the nodes in an independent set with maximum degree, called targeted immunization in the independent set. When the total degree of immune nodes in independent set is equal to the total degree of targeted immunization nodes in the whole network, the immunization strategy of independent set is more effective than the targeted immunization strategy of the whole network. Based on the network structure, this paper explains the reason. Comparing the random immunization of independent sets with the random immunization in the whole network, test results indicate that more nodes do not be removed with high degree for the random immunization of independent sets. For classic susceptible-infected(SI) model, all nodes in the network are only two states: susceptible or infected. In the study of immunization strategies, comparing SI model with SIR, SIS models. The use of SI model will be more favorable.     

Trust in Virtual Enterprise：Determinants and Mechanism

Trust is the most basic operation mechanism. From the embedded visual angle, the cooperation relation is considered as the inter-continuation.The trust relation in virtual enterprise is embedded in the network of social relation and will evolve dynamically. The interaction between partners, which is composed of information communion and learning, plays an important role in the creation mechanism of VE's trust . Firstly, this article starts with the time dimension of cooperation relation in VE, compartmentalizes the trust relation of VE as two parts: initial trust and continuous trust. Secondly, it argues that the prior experience of cooperation, reputation and commitment can affect the initial trust obviously, accordingly, the life cycle of VE, opportunism, interdependence and the distance of culture and geographic distribution can determine the generation and development of the continuous trust. Finally, it develops a dynamic process model based on information communion and learning, which perfects Nielsen's static conception model.     

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.     

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.     

用模糊神经网络提高洪峰预报精度的研究

在大量研究的基础上,提出了基于模糊理论的神经网络改进算法,用来提高对洪峰的预报精度。该方法在网络训练时引入模糊理论来确定网络误差修改的程度。引入的算法增大了大值输出样本和期望输出的误差,使得网络向着提高洪峰拟合精度的方向修改权重。应用表明,改进的模糊BP神经网络能够较好的反映洪水演进机理,提高了神经网络洪水预报模型对洪峰的预报精度,保证了洪峰预报的可靠性。     

AN APPROACH TO SHARE DISTRIBUTED RESOURCES IN A LOCAL AREA NETWORK

An algorithm of sharing distributed resoumes in a local area network is proposed , which is based on Queuing theory and statistics of probability. It is proved by means of a emulative program that this algorithm is simple, feasible and applicable.     

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。