With the development of embedded systems, people tend to abstract the capacity of an embedded equipment as a service in order to simplify the development, deployment, management and maintenance of the embedded software. By aggregating abilities of individual embedded devices via service composition, people can easily build a more reliable and efficient system. Although the service composition problem has been extensively studied in the field of Web, the adoptation of service composition technique to embedded devices stumps due to the resource limitation and platform heterogeneity of embedded systems. To address these problems, this paper builds a service composition engine for embedded systems that comprises three main works: First, this paper provides a uniform method to represent the embedded service composition problem. Second, this paper designs a compiling method based on topological sorting to convert the unified composition information into the service composition file that represents the way to implement the composite service. Third, this paper devises a bytecode virtual machine to execute the service composition file, and implements the composite service in a resource-friendly way. At last, a carefully devised experiment is conducted, and the result shows our devised engine provides a lightweight, reliable and well-performed way to realize the service composition technique on embedded devices.

针对网络控制平面可能被迫设置较低信道比特率和改进调制格式的问题,文章提出了一种基于模糊C均值(FCM)的认知算法,在软件定义光网络(SDON)中进行学习和决策制定.首先,将FCM算法加入到SDON控制平面,以实现比非认知性控制平面更好的网络性能;然后,利用FCM算法,根据光信道传输质量,实时和自主地确定高速灵活速率的转发器的调制格式;最后,通过长距离传输网络的计算模拟,对FCM算法的性能进行了评价,并将其与SDON中常用的基于案例的推理(CBR)算法进行了比较.结果表明,与CBR算法相比,FCM算法在快速性和误差避免方面性能更优.

声表面波(SAW)谐振器已广泛应用于各种无线传感器中,为了实现高更新率、高精度的SAW测量,该文提出了一种基于低成本六端口的谐振式SAW查询系统.通过低成本六端口干涉仪,精确快速地测定无源SAW谐振器的频率.利用延迟线,将频率测量值简化为可通过六端口网络进行即时评估的相位测量值,即将引入的相移与非延迟信号进行比较获得频率估计.研究结果表明,与传统设计相比,所提设计不需进行复杂的信号处理,可提供高更新率,且系统成本较低.2.4 GHz频带的实验证明了所提设计的可行性和优越性,实现的精度较高,且测量时间仅需约3μs.

The TENA-HLA gateway can accomplish data exchange between"Modeling and Simulation of high-level system architecture HLA" and "The Test and Training Enabling Architecture TENA" and make it barrier-free to deliver information. Nowadays, many existing gateways are implemented in such a way that a master program re-ceives and delivers data circularly which has been translated by an intermediate conversion to another network. However, the intermediate conversion is not application specific and is too complex for only a small amount of basic conversion files. We propose a design for the gateway software, according to the mapping rules between TENA ob-jects and HLA objects specified by user;combining with TDL and FED compiling technologies, it generates the ap-plication specific gateway software automatically. We also give experimental results and their analysis in the paper.

The introduction of the full paper discusses that the influence of weak ties to Information Spreading in online social network are different according to different online social network type. In the information exchanged social networks, removing the weak ties have little influence on the information spreading, while in the relationship social network, removing the weak ties have significant influence on the information spreading. An efficient weak ties evaluation algorithm can more accurately find the weak ties in a social network to improve the control effect of information spreading. We study the weak ties evaluation algorithm, use the concept of clustering coefficient between two friends and the global evolution to optimize the initial algorithm, in order to solve some existed problem in the initial algorithm. Analysis and experiences proved that the new algorithm perform better than the initial algorithm and the weak ties are more effective on the information spreading in online social network, but the new algorithm still has little influence on the information spreading in the information exchanged social networks.

A passive monitoring model of P2P specific information based on data verify algorithm is presented.Taking P2P specific information as the object,A two-dimensional Bloom Filter algorithm is used to verify data as the judgment reference.To analyze two-dimensional Bloom Filter algorithm's time performance,space performance and misjudgment rate,the algorithm compensates the current data verify algorithm's defect of taking more memory space and with low efficiency.Two-dimensional Bloom Filter algorithm can meet the performance requirement of passive monitoring model to data verify algorithm.

Faulty links are a typical network fault symptom in wireless sensor network.It affected the operation of network and the quality of service seriously,therefore faulty links need to be detected and repaired.Localization technique of faulty links based on simple network tomography was introduced.This paper presented a binary disjunctive model for describing link faulty states;the localization problem of faulty links is referred to as the Maximum A-posteriori Probability problem.By making the Localization problem of faulty links mapped to weighting minimal set-cover problem,the algorithm based on heuristic strategy was proposed.The performance of inference algorithm was evaluated by simulation,and the simulation results indicated the feasibility and efficiency of the method.

As a kind of prior knowledge,link state probability distribution plays an important role in inferring the accuracy of link performance state.This paper deals with the inference of internal link state probability based on the end-to-end measurement in tree topology,and defines it as a maximum likelihood estimation problem.By using a product model to describe the relationship between the path and the link state probability and by estimating link state probability via the computation of path state probability,a new approach to the fast inference of link state probability is proposed.The approach is then applied to simulation experiments.The results indicate that the proposed approach is effective and practical in inferring the internal link state probability.

Faulty components in a wireless sensor network need to be localized and repaired to sustain the normal operation of the network. Due to the inherent stringent bandwidth and energy constraints, we consider only use end-to-end measurement to infer lossy links in sensor network. In this paper, we formulate the problem of lossy links localization as a Bayesian inference problem, and use max-product algorithm to solve it. Finally, we evaluate the performance of our approach through simulation and it shows good performance and stability.

This paper studies identification of lossiest links based on Boolean Network Tomography. It addresses this problem of identification of lossiest links to the most probable explanation in Bayes estimation. A method using link state prior probability is presented to inferred lossiest network links, the presented method computes posteriori conditional probability of each candidate link assignments and chooses the assignment with maximum probability. Theoretic analysis proves that the method is feasible, and simulation results show that the method achieves accuracy higher than previously proposed heuristic methods.

网络节点的不断运动造成Ad Hoc网络拓扑的动态性。描述和量化动态性是设计、仿真以及测量Ad Hoc网络的基础。首先推导出Ad Hoc网络的链路持续时间分布和拓扑持续时间分布的计算公式,并进行了仿真验证。然后提出利用TTL值感知拓扑变化的方法,并研究了此方法的感知率。最后基于以上结果,提出将网络断层扫描技术应用于Ad Hoc网络时,在测量时间内网络拓扑不发生变化的概率计算公式,并在Ad Hoc网络步行速度场景下给出了仿真结果。研究结果为Ad Hoc网络动态性和端到端测量技术研究提供基础。

The technology of wireless sensor network has matured and has been built actual applications such as environment monitoring,surveillance etc.The experiences have demonstrated the obvious need for network failure managing tools.Lossy links use in a sensor network affect network performance,and hence need to be detected and repaired.Sensor nodes are restrained by limited resources,so inference technique based on network tomography is introduced by passive end-to-end measurement.Through the problem of lossy links inference is mapped to minimal set-cover problem,the algorithm based on heuristic strategy is proposed. The performance of inference algorithm is evaluated by simulation,and the simulation results indicate feasibility and efficiency of the method.

Without the cooperation of internal nodes, the traceroute-based approaches and the SNMP-based approaches will fail to identify the routing topology of the work. Meanwhile, network tomography techniques can infer the logical topology of network without the cooperation of nodes, but loss part information of the routing topology. This paper proposes a new methodology to infer the hop count of the shared path of destinations based on the end-to-end measurements named digging measurement framework, which consists of a series of sandwich probing with different the initial TTL value of the large packet, for each 1-by-2 component and then the routing topology can be inferred by the hop count tree glassification algorithm. The methodology has higher accuracy and efficiency and is validated by the simulation results and the Internet experiences.

In order to facilitate the support of multiple networks and enable plug and play at the sensor level, based on analyzing the features of networked sensor , used the feature of CAN fieldbus's real-time performance, a smart network transducer based on CAN fieldbus is designed.The infrastructure, implement methods of hardware and software of this new type sensor are described.

This paper focuses on the multiple source, multiple destination network tomography problem. The main contributions are as follows. First, the performance stable delay difference measured by the back-to-back packet pair with different size is used firstly as path metrics to identify the topology. Second, this paper proposes a novel probing meathead to infer the hop count of the shared path for each 1-by-2 component and each 2-by-1 component. Third, with the novel methodology, we firstly resolve the key problem of routing topology identification by multiple sources network tomography. The accuracy and efficiency of methodology is validated by the simulation results.

In recent years, Botnet has been one of the emerging serious threats to the Internet and attracted wide atten- tion from researchers. By analyzing the characteristics of abnormal behavior shown by Botnet at its different stages, the paper proposes a Botnet-detecting method based on abnormal-behavior-monitoring, describes the principle and the struc- tural framework of the system, including the design and implementation of its key technology.

The early fault of aircrafts′ engine structural systems was analyzed.The early fault classification and recognition method that combines wavelet transformation and fractual theory with fuzzy neural network(FNN) was put forward.Wavelet transformation was applied to the processing.Fractal theory was used to extract early fault information.Then FNN was utilized to recognize and classify the early fault feature information.Experimental results indicate that the classification and recognition method is an effective method for recognizing early faults.