Design of Aided Decision-Making Program for Prioritizing Construction Projects in Urban Road Network Planning

The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rolled method are chosen as the theoretical foundations of the program, and then benefit model is improved to accord with the actuality of urban traffic in China. Consequently, program flows, module functions and data structures are designed, and particularly an original data structure of road ...

渤海砺兵练“打赢”

七月,首都民兵预备役高炮部队在烈日炎炎的渤海某地高炮靶场进行了防空演练。通过演练,检验了部队科技练兵成果,进一步提高了预备役部队官后防空作战能力。

Prediction of Injection-Production Ratio with BP Neural Network

Injection of water to enhance oil production is commonplace, and improvements in understanding the process are economically important. This study examines predictive models of the injection-to-production ratio. Firstly, the error between the fitting and actual injection-production ratio is calculated with such methods as the injection-production ratio and water-oil ratio method, the material balance method, the multiple regression method, the gray theory GM (1,1) model and the back-propogation (BP) neural network method by computer applications in this paper. The relative average errors calculated are respectively 1.67%, 1.08%, 19.2%, 1.38% and 0.88%. Secondly, the reasons for the errors from different prediction methods are analyzed theoretically, indicating that the prediction precision of the BP neural network method is high, and that it has a better self-adaptability, so that it can reflect the internal relationship between the injection-production ratio and the influencing factors. Therefore, the BP neural network method is suitable to the prediction of injection-production ratio.

Synthesis of Petri net supervisors enforcing general constraints

This paper deals with the synthesis of Petri net supervisor enforcing the more expressive constraints including marking terms, firing vector terms and Parikh vector terms. The method is developed to handle uncontrollable and unobservable transitions existing in the constraints. The “greater-than or equal” general constraints can also be transformed into “less-than or equal” Parikh constraints. An example is analyzed to show how the problem is solved. General constraint is first transformed into Parikh vector constraints, and Matrix-Transformation is proposed to obtain the admissible constraints without uncontrollable and unobservable transitions. Then the supervisor can be constructed based on constraints only consisting of Parikh vector terms. The method is proved to be more concise and effective than the method presented by Iordache and Moody especially when applied to large scale systems.

Dynamic Adaptive Finite Element Analysis of Acoustic Wave Propagation Due to Underwater Explosion for Fluid-structure Interaction Problems

In this paper, an investigation into the propagation of far field explosion waves in water and their effects on nearby structures are carried out. For the far field structure, the motion of the fluid surrounding the structure may be assumed small, allowing linearization of the governing fluid equations. A complete analysis of the problem must involve simultaneous solution of the dynamic response of the structure and the propagation of explosion wave in the surrounding fluid. In this study, a dynamic adaptive finite element procedure is proposed. Its application to the solution of a 2D fluid-structure interaction is investigated in the time domain. The research includes：a） calculation of the far-field scatter wave due to underwater explosion including solution of the time-depended acoustic wave equation, b） fluid-structure interaction analysis using coupled Euler-Lagrangian approach, and c） adaptive finite element procedures employing error estimates, and re-meshing. The temporal mesh adaptation is achieved by local regeneration of the grid using a time-dependent error indicator based on curvature of pressure function. As a result, the overall response is better predicted by a moving mesh than an equivalent uniform mesh. In addition, the cost of computation for large problems is reduced while the accuracy is improved.

Deterministic and randomized scheduling problems under the lp norm on two identical machines

Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in large-size computing, task arrangement in flexible manufacturing systems, etc., are multiprocessor scheduling problem. In the traditional parallel machine scheduling problems, it is assumed that the problems are considered in offline or online environment. But in practice, problems are often not really offline or online but somehow in-between. This means that, with respect to the online problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi-online ones. In this paper, the semi-online problem P2|decr|lp (p>1) is considered where jobs come in non-increasing order of their processing times and the objective is to minimize the sum of the lp norm of every machine’s load. It is shown that LS algorithm is optimal for any lp norm, which extends the results known in the literature. Furthermore, randomized lower bounds for the problems P2|online|lp and P2|decr|lp are presented.

Vehicular Beacon Broadcast Scheduling Based on Age of Information(AoI)

Vehicular beaconing plays an important role to facilitate various applications in the paradigm of Internet of Vehicles(IoV). Due to high dynamic and resource limitation in IoV, how to schedule the vehicular beacon broadcast is challenging, especially in dense scenarios. In this paper, we investigate the beacon broadcast scheduling problem considering the Age of Information(AoI). We first propose an algorithm minimizing the expected sum of AoI considering the limited communication resource and vehicle mobility. Then the performance of the proposed algorithm is analyzed. With the proposed algorithm, the optimal solution can be obtained under certain conditions. Extensive simulations are conducted to verify the efficiency, effectiveness and fairness of the proposed solution.

Stochastic Lattice gas Cellular Automata Model for Epidemics

The aim of this study was to develop and explore a stochastic lattice gas cellular automata （LGCA） model for epidemics. A computer program was development in order to implement the model. An irregular grid of cells was used. A susceptible-infected-recovered （SIR） scheme was represented. Stochasticity was generated by Monte Carlo method. Dynamics of model was explored by numerical simulations. Model achieves to represent the typical SIR prevalence curve. Performed simulations also show how infection, mobility and distribution of infected individuals may influence the dynamics of propagation. This simple theoretical model might be a basis for developing more realistic designs.

Online Internet Traffic Identification Algorithm Based on Multistage Classifier

Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.

The analysis of application of data mining technology in the system of intrusion detection

With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Internet has the features of interaction, openness, sharing and so on. However, during the daily commerce, people worry about the security of the network system. So a new technology which can detect the unusual behavior in time has been invented in order to protect the security of network system. The system of intrusion detection needs a lot of new technology to protect the data of the network system. The application of data mining technology in the system of intrusion detection can provide a better assistant to the users to analyze the data and improve the accuracy of the checking system.

Modeling and Characterizing Internet Backbone Traffic

With enormous growth of the number of Internet users and appearance of new applications, characterization of Internet traffic has attracted more and more attention and has become one of the major challenging issues in telecommunication network over the past few years. In this paper, we study the network traffic pattern of the aggregate traffic and of specific application traffic, especially the popular applications such as P2P, VoIP that contribute most network traffic. Our study verified that majority Internet backbone traffic is contributed by a small portion of users and a power function can be used to approximate the contribution of each user to the overall traffic. We show that P2P applications are the dominant traffic contributor in current Internet Backbone of China. In addition, we selectively present the traffic pattern of different applications in detail.

Exploring Application Layer Protocol Relationships in SoftSwitch

Relationships between application layer protocols in softswitch are explored in this paper.Two notions, i.e.protocol relationship and protocol grouping, are proposed, which are not clearly defined and even not paid much attention to before.On the basis of a well known protocol relationship named protocol conversion, three novel protocol relationships including protocol collaboration relationship, protocol cooperation relationship and protocol independent relationship are presented, so that protocol relationships are classified into four types.According to the functionality and purpose of each protocol, main protocols related to softswitch are divided into five groups.As to protocol conversion in softswitch, information flow trail(IFT) is utilized to facilitate problem solving.A decision rule for protocol conversion mode is proposed to guide how to choose between direct conversion and indirect conversion.A property of protocol relationships in softswitch is induced from all kinds of service scenarios of softswitch.This property summarizes protocol relationships within each protocol group or between two specific protocol groups.A merit of protocol grouping together with classification of protocol relationship is also presented.The effort of this paper pushes the protocol engineering to go ahead.

AN ADAPTIVE-WEIGHTED TWO-DIMENSIONAL DATA AGGREGATION ALGORITHM FOR CLUSTERED WIRELESS SENSOR NETWORKS

In this paper,an Adaptive-Weighted Time-Dimensional and Space-Dimensional(AWTDSD) data aggregation algorithm for a clustered sensor network is proposed for prolonging the lifetime of the network as well as improving the accuracy of the data gathered in the network.AWTDSD contains three phases:(1) the time-dimensional aggregation phase for eliminating the data redundancy;(2) the adaptive-weighted aggregation phase for further aggregating the data as well as improving the accuracy of the aggregated data; and(3) the space-dimensional aggregation phase for reducing the size and the amount of the data transmission to the base station.AWTDSD utilizes the correlations between the sensed data for reducing the data transmission and increasing the data accuracy as well.Experimental result shows that AWTDSD can not only save almost a half of the total energy consumption but also greatly increase the accuracy of the data monitored by the sensors in the clustered network.

Structural Insights on Internet Traffic:Community Overlapping and Correlations

There is an increasing number of Internet applications, which leads to an increasing network capacity and availability. Internet traffic characterisation and application identification are, therefore, more important for efficient network management. In this paper, we construct flow graphs from detailed Internet traffic data collected from the public networks of Internet Service Providers. We analyse the community structures of the flow graph that is naturally formed by different applications. The community size, degree distribution of the community, and community overlap of 10 Internet applications are investigated. We further study the correlations between the communities from different applications. Our results provide deep insights into the behaviour Internet applications and traffic, which is helpful for both network management and user behaviour analysis.

AN IDENTITY-BASED KEY AGREEMENT SCHEME FOR LARGE SCALE SENSOR NETWORKS

To solve the problems of high memory occupation, low connectivity and poor resiliency against node capture, which existing in the random key pre-distribution techniques while applying to the large scale Wireless Sensor Networks （WSNs）, an Identity-Based Key Agreement Scheme （IBKAS） is proposed based on identity-based encryption and Elliptic Curve Diffie-Hellman （ECDH）. IBKAS can resist man-in-the-middle attacks and node-capture attacks through encrypting the key agreement parameters using identity-based encryption. Theoretical analysis indicates that comparing to the random key pre-distribution techniques, IBKAS achieves significant improvement in key connectivity, communication overhead, memory occupation, and security strength, and also enables efficient secure rekcying and network expansion. Furthermore, we implement IBKAS for TinyOS-2.1.2 based on the MICA2 motes, and the experiment results demonstrate that IBKAS is feasible for infrequent key distribution and rekeying for large scale sensor networks.

Modeling and Analyzing Web Application with Aspect-Oriented Hierarchical Coloured Petri Nets

Aspect-oriented modeling can uncover potential design faults, yet most existing work fails to achieve both separation and composition in a natural and succinct way. This study presents an aspect-oriented modeling and analysis approach with hierarchical Coloured Petri Nets(HCPN). HCPN has sub-models and well-defined semantics combining a set of submodels. These two characteristics of HCPN are nicely integrated into aspect oriented modeling. Submodels are used to model aspects while the combination mechanism contributes to aspects weaving. Furthermore, the woven aspect oriented HCPN model can be simulated and analyzed by the CPN Tools. A systematic web application case study is conducted. The results show the system original properties are satisfied after weaving aspects and all design flaws are revealed. As such, the approach can support web application design and analysis in an aspect-oriented fashion concisely and effectively.

Auto Distribution of Tag Table in P2P Control System

In control system, tag table is like a dictionary mapping tagname to address. Therefore, applications on workstation may use tagname to access different data in system. Normally tag table generated by configuration software will transfer to other workstation in system manually after system configuration, which is inconvenient and failible. The development of peer-to-peer （P2P） network technology and the realization of control system based on P2P network make the auto distn＇bution of tag table possible. In this paper based on file sharing technology the presented method realizes the auto distn＇bution of tag table.

A Survey on Smart Collaborative Identifier Networks

The current Internet architecture was designed on the basis of a triple bindings model, which could meet the needs of the early Internet. However, with the tremendous growth of the Internet and the continuous innovations of applications, the triple bindings(namely, control/data binding, resource/location binding and user/network binding) have given rise to many problems for the Internet, such as scalability, mobility, and security. In order to solve these problems, many network techniques have been developed. Besides, novel future Internet architectures including Information-Centric Networks and Software-Defined Networks have emerged. However, these architectures only partially decouple the triple bindings. To completely separate the triple bindings, Smart Collaborative Identifier Networks(SINET) is proposed. There have been many research efforts on SINET, which built the foundation of SINET being a promising future Internet. In this paper, we comprehensively introduce SINET and these related research works. We start by introducing the motivation for SINET, explain its fundamental concepts and how it can make a difference. Next, we present in details the design principles of every layer in SINET, explaining how it can decouple the triple bindings and solve the problems of the current Internet. Finally, we discuss the state-of-theart challenges in SINET. We investigate the ongoing research works and commercial products in SINET, with aspects such as scalability, mobility, security and reliability.

Quality of service estimation based on maximum bottleneck algorithm for domain aggregation in backbone networks

This paper investigates the routing among autonomous systems (ASs) with quality of service (QoS) requirements. To avoid the intractability of the problem, abstract QoS capability must be informed among ASs, because the routhing which constrained QoS has been proved to be nondeterministic polynomial-time (NP) hard even inside an AS. This paper employs the modified Dijkstra algorithm to compute the maximum bottleneck bandwidth inside an AS. This approach lays a basis for the AS-level switching capability on which interdomain advertisement can be performed. Furthermore, the paper models the aggregated traffic in backbone network with fractional Brownian motion (FBM), and by integrating along the time axis in short intervals, a good estimation of the distribution of queue length in the next short intervals can be obtained. The proposed advertisement mechanism can be easily implemented with the current interdomain routing protocols. Numerical study indicates that the presented scheme is effective and feasible.