基于有色Petri网的网络化传感系统研究

为提高传感器网络兼容性和互换性,构建了一种基于IEEE 1451的通用网络化传感系统模型,能够实现传感器的即插即用。基于Petri网建立模型,利用CPN Tools对其进行形式化建模、分析和验证。结果表明,该系统的有界性、活性等特性均可用,可实现网络化传感系统快速化、标准化的建立。所建立的系统模型能够为研制工业现场中所需要的具体的网络化智能传感器提供理论依据,能更好地实现其系统网络兼容性和互换性等特性,可以在各领域广泛地应用。

基于UML和Petri网的网络化传感系统模型研究

为了提高网络化传感系统的网络兼容性和互换性,基于国际通用接口技术标准IEEE 1451和传感器的原理与特点,利用UML和Petri网分别从静态建模、系统部署图和动态建模构建了一种网络化传感系统模型。该模型能够通过CPN tools动态行为验证,可对研制智能传感器模型进行简化与优化,能够实现良好的网络互操作性和"即插即用"功能。

网络化智能传感技术发展浅析

网络化智能传感技术是智能传感技术和计算机网络技术结合的产物。本文介绍了基于现场总线和IEEEP1451标准族的智能传感技术的发展现状,提出基于IEEEP1451智能变送器接口标准族的智能传感技术是未来网络化智能传感技术的发展方向。

基于IEEE1451标准的IP传感器的设计与实现

基于简化的 IEEE1451 智能传感器信息模型,提出了基于嵌入式Internet技术的 IP传感器模型,并进行了原型实现。分析了IP传感器的网络时延问题,并在网络环境下对其时延性能进行了测试。实验结果表明,所设计的IP传感器可广泛应用于分布式网络化传感、测量和控制系统。

Securing Sensor Networks Based on Optimization of Weighted Confidence

In this paper, an optimized rmlicious nodes detection algorithm, based on Weighted Confidence Filter （WCF）, is proposed to protect sensor networks from attacks. In this algorithm, each cluster head in a cluster-based hierarchical network figures out an average confidence degree by means of messages from its child nodes. The cluster head only accepts a message from the child node whose confidence degree is higher than the average. Meanwhile, it updates the confidence degrees for each of its child nodes by comparing the aggregation value and the received messages, and regards them as the weight of exactness of messages from nodes. A sensor node is judged to be rmlicious if its weight value is lower than the predefined threshold. Comparative simulation results verify that the proposed WCF algorithm is better than the Weighted Trust Evaluation （WTE） in terms of the detection ratio and the false alarm ratio. More specifically, with the WCF, the detection ratio is significantly improved and the false alarm ratio is observably reduced, especially when the malicious node ratio is 0.25 or greater. When 40% of 100 sensors are malicious, the detection accuracy is above 90% and the false alarm ratio is nearly only 1.8%.

Fuzzy Neural Network Model of 4-CBA Concentration for Industrial Purified Terephthalic Acid Oxidation Process

A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.

Multi-objective optimization sensor node scheduling for target tracking in wireless sensor network

Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

Energy-Efficient Distributed Lifetime Optimizing Scheme for Wireless Sensor Networks

In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired coverage can be derived considering the scale of deployment area and the number of sensor nodes. Base on the coverage analysis, an energy-efficient distributed node scheduling scheme is proposed to prolong the network lifetime while maintaining the desired sensing coverage, which does not need the geographic or neighbor information of nodes. The proposed scheme can also handle uneven distribution, and it is robust against node failures. Theoretical and simulation results demonstrate its efficiency and usefulness.

An evolutionary game based security decision algorithm for wireless sensor networks

When using traditional game methods to study information security of the wireless sensor networks,players are mostly based on the assumption of completely rational.Based on bounded rationality,the evolutionary game theory is used to establish the attack-defense model,analyze the strategy selection process of players,solve the evolutionarily stable strategy and design the optimal strategy selection algorithm.Then,considering the strategy dependence,the incentive and punishment mechanism is introduced to improve the replicator dynamic equation.The simulation results show that the model is reasonable and the algorithm is effective,which provides new theoretical support for the security of wireless sensor networks.

Design of IEEE1451.5 WTIM for Industrial Network Based on Ubiquitous Sensor Network

Recently, the use of ubiquitous sensor network technology has spread vastly. The ubiquitous sensor networks are widely de- ployed in factory auttxnation as they provide effective measuring solution for instruments. The wired/wireless network module, which provides the interface to connect to the u-sensor network, is needed but there is no perfect standardization about the interface. In this situation, the interface compatibility between measuring instrument can be maintained using the IEEEI451 international standard. In this paper, the Wireless Transducer Interface Mcduie （WTIM） based on IEEE1451.5 was designed. It coxnects to the measuring instnmnt, like the muiti-meter, power meter, and etc., to support the RS232 interface. As these devices cannot connect to network without a mod- ule, we use the WTIM to help these devices connect to network sys- ton. Its ftmction was verified through the ubiquitous network connection and data transfer between monitoring PC and measuring instrument. This technology is expected to reduce cost in order to construct the wireless industry automation system using existing devices.

Dynamically Optimized Sensor Deployment Based on Game Theory

Sensor network deployment is the key for sensors to play an important performance. Based on game theory, first, the authors propose a multi-type sensor target allocation method for the autonomous deployment of sensors, considering exploration cost, target detection value, exploration ability and other factors. Then, aiming at the unfavorable environment, e.g., obstacles and enemy interference, the authors design a method to maintain the connectivity of sensor network, under the conditions of effective detection of the targets. Simulation result shows that the proposed deployment strategy can achieve the dynamic optimization deployment under complex conditions.

Optimized algorithm for balancing clusters in wireless sensor networks

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions in-cluding computation capability and battery capacity.Topology control is an important issue for achieving a balanced placement of sensor nodes.The clustering scheme is a widely known and efficient means of topology control for transmitting information to the base station in two hops.The automatic routing scheme of the self-organizing technique is another critical element of wireless sensor networks.In this paper we propose an optimal algorithm with cluster balance taken into consideration,and compare it with three well known and widely used approaches,i.e.,LEACH,MEER,and VAP-E,in performance evaluation.Experimental results show that the proposed approach increases the overall network lifetime,indicating that the amount of energy required for com-munication to the base station will be reduced for locating an optimal cluster.