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• 2010, No. 6　Published:01 June 2010 Last issue    Next issue
  Columns in this issue: 论文

• 论文

  Agent,Goal and Scenario Integrated Requirement Analysis Methodology

  LIU Lin1,MAO Xinjun2

  2010, 32(6): 1-8. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 620 )   PDF (591KB) ( 419 )   　　

  This paper sets out from the agentoriented software engineering paradigm, proposes an requirement analysis methodology integrating with agent, goal and scenario technology. In the proposed approach, system inputs are textual descriptions of the interactions between various agents within the system and the environment, annotated with informations on intended purpose of the scenarios. At the beginning stage of the proposed AOA method, original scenarios in SSDL are described by endusers. These scenarios are then transformed into an internal representation  ScenarioTree. Then an inductive learning procedure will be started, during which the scenario descriptions are decomposed, clustered, and generalised. The learning result is an abstract grammar  an attribute grammar. The attributes and attribute computing rules are used to reinforce the expressiveness of the grammar.

  A Power Management Mechanism for Wireless Sensor Networks Used by Mobile Agents

  HUANG Haiping，WANG Ruchuan，SUN Lijuan，SHA Chao

  2010, 32(6): 9-12. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 800 )   PDF (559KB) ( 436 )   　　

  Aimed at the remarkable characteristics of power restriction on wireless sensor networks, it is essential to resolve the issue on effective power management. Currently,plenty of research work runs short of integrity because it only considers powersaving from one of the following techniques such as the topology control mechanism, the rooting protocol or the data aggregation algorithm, but not to measure the power consumption of the whole network. With the introduction of mobile agents, it discusses the power management of the sensor networks from several points such as topology control and cluster forming, and data collection. Some novel algorithms based on mobile agents for power management are proposed. Based on simulation and  performance analysis on power consumption, balancing the communication flows and the whole networks’ lifespan, it analyzes the advantages, disadvantages and feasibility of these algorithms.

  The Effect of the DHT Design on the Maintenance Cost Induced by Churn

  HUANG Qingfeng,LI Zhitang

  2010, 32(6): 13-15. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 507 )   PDF (379KB) ( 365 )   　　

  In the structured peertopeer network,the churn caused by nodes’ joining and leaving frequently increases the cost of updating the routing table. With the problem of churn,which is difficult to handle by DHT,the concept of inverseneighbor nodes is proposed. This  means the node is in their routing tables. The number of inverseneighbor nodes for six DHT networks is computed. We find that the most significant factors affecting churn are routing, neighboring nodes selection, bootstrapping and the recovery policy,and the parallel lookup. In any two existing DHTs, there are at least two different policies in the five policies . Therefore, the method that compares the routing tables update costs of two structured p2p network directly cannot decide which policy can deal with churn better, so we propose a new method of analysis: CSP. By improving the existing DHTs,we compare each different policies by CSP. The experimental results suggest that iterative routing, fast bootstrapping, periodic recovery,and the effective neighboring nodes selection algorithm can decrease the cost of updating the routing tables in high churn.

  Adaptive Scheme of Power Saving in the IEEE 802.16 Systems

  ZHOU Xiangjun

  2010, 32(6): 16-18. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 427 )   PDF (555KB) ( 360 )   　　

  An adaptive scheme of power saving is proposed for the voice over IP (VoIP) services, which are based on the adaptive multirate (AMR) speech codec in the IEEE 802.16 systems. This scheme determines whether both of the uplink and downlink services enter the silence period through examining the information of speech frames in the twoway conversation periodically. Based on this, the parameters of the power saving mode are modified adaptively. Then the performance of the proposed scheme in terms of energy saving, drop rate and signaling overhead of system is analyzed. In addition, the simulation experiments are implemented. Through the theoretical analysis and simulation results, the new scheme shows that it reduces the energy consumption by more than 13.4% based on guaranteeing the drop rate of users compared with the conventional scheme.

  Research of a Mobile Agent Secure Model Based on Distributed Trusted Measurement

  WU Xiaoping1，XING Honggen2，SHEN Zhidong3

  2010, 32(6): 19-21. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 561 )   PDF (416KB) ( 453 )   　　

  This paper discusses a security scheme of mobile agents on the trusted computing platform. The security architecture of mobile agents based on trusted measurement is constructed by using the trusted measurement policy and the trust chain mechanism provided by the trusted computing platform. Furthermore, a mathematical model of trust relationship is also constructed among the mobile agent platforms based on trusted measurement in the distributed computing environment of mobile agents. Then the experimental numerical value simulation and test validation are performed.

  A Method of Generating the MultiTargets Attack Graphs Based on Greedy Policies

  ZHU Ming1，YIN Jianping1，CHENG Jieren1,2，LIU Qiang1，LIN Jiarun1

  2010, 32(6): 22-25. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 590 )   PDF (432KB) ( 506 )   　　

  In order to avoid the combination of states occurred in the generation of attack graphs while analyzing network vulnerabilities and to make the attack graphs available for analyzing the multitargets’ vulnerabilities, a new method of generating attack graphs based on greedy policies is proposed. The method introduces the  network node correlations, uses greedy policies to reduce the amount of vulnerabilities, chooses the attack routes that allow attackers to gain network node priority with the greatest potential and generate the attack graphs with those attack routes. The algorithm analysis and the experimental results show that the cost of time and space of the method is the polynomial level of the network node number and the network node correlation number, which means it has solved the problem of the great combination of states effectively. The attack graph it generates covers all network nodes that attackers can access, so the method can be used to analyze the multitargets’ vulnerabilities.

  An Approach to Accessing VANETs Based on Rough Sets

  DONG Tianzhe,LIU Yanheng,WANG Jian,ZHANG Jing

  2010, 32(6): 26-29. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 625 )   PDF (557KB) ( 306 )   　　

  With the rapid development and the extensive application of vehicular ad hoc networks(VANET), the problem of  how to ensure the credibility of the vehicular endpoints during access authentication has become the research focus. Because the rough set theory is suitable for handling uncertain information, we propose a new approach to accessing VANETs based on the rough set theory. The mobile trusted module(MTM) on endpoints in VANETs is used for collecting the trusted attribute information, and the final accessing decisions can be made. The experimental results show the  effectiveness and practicality of this method.

  Research on the MultiSensor Data Fusion Technology  for Network Security

  LIN Jiarun1，YIN Jianping1，CHENG Jieren1，2，LONG Jun1，ZHU Ming1

  2010, 32(6): 30-33. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 742 )   PDF (388KB) ( 680 )   　　

  The multisensor data fusion technology is one of the hotest topics in the area of network security in recent years.In this paper, a new method of classifying data fusion based on time and space is proposed. Then, comparisons and analysis of various fusion technologies applied in the distributed intrusion detection system and the network security awareness system are given. Finally the development trend of the multisensor data fusion technology in network security is discussed.

  Reserch of Intrusion Detection Based on the BP Networks and the Improved PSO Algorithm

  SHEN Xueli,ZHANG Jisuo

  2010, 32(6): 34-36. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 544 )   PDF (390KB) ( 376 )   　　

  This paper shows a way that combines the BP networks with the improved PSO algorithm aiming at false positive rate in intrusion detection systems(IDS).Based on the characteristics of the local precise search of the BP networks and the global search of the improved PSO algorithm, this method optimizes the weight and threshold of the BP networks, conquers the disadvantages of the BP networks that are easily trapped in the local extremum. And the network structure is applied into intrusion detection systems, which can discover the known detection exactly, forecast the new detection ,and reduce the invasion of omissions and the false alarm rate. Comparing the simulation results of the KDD99 CUP dataset with the intrusion detection system based on the traditional BP networks and the improved PSOBP network algorithm, the improved PSO algorithm shows less iteration times, quicker convergence rate,higher detection rate ,and sufficient availability.

  Based on Neural Networks and the CFSBased Feature Selection

  SUN Ningqing

  2010, 32(6): 37-39. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 683 )   PDF (397KB) ( 613 )   　　

  This paper introduces a novel intrusion detection model based on neural networks and the CFS (correlationbased feature selection) based feature selection mechanism. It can effectively detect several types of attacks by combining neural networks and the CFSbased feature selection. The experiments upon the wellknown KDD Cup 1999 intrusion detection dataset demonstrate that the model is actually effective in practice.

  Research of a Decentralized Workflow Management Architecture Based on the Status Information

  WU Ling,MA Ji

  2010, 32(6): 40-44. doi: 10.3969/j.issn.1007130X.2010

  Abstract ( 614 )   PDF (992KB) ( 513 )   　　

  The traditional workflow management systems are often based on the server/client model. In this architecture the server can be the bottleneck when lots of workflow is running. When the server is down, all the workflow can not  execute any more. The paper puts forward a decentralized workflow management system model based on the status information. It processes workflow according to the status information. The status information and the trigger event are used to judge the execution condition and the status. Tokens are used to solve the resource competition. There is no independent mechanism to destribute jobs. No host will be the performance bottleneck. The paper discusses the architecture design, key technologies  and system implementation. The architecture provides a new management and control model for complicated workflow.

  A Study of the Robust Fuzzy CMeans Algorithm  for Image Segmentation

  ZHANG Hui

  2010, 32(6): 45-47. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 626 )   PDF (345KB) ( 487 )   　　

  Fuzzy C-means clustering is one of the important learning algorithms in the field of pattern recognition, which has been applied early to image segmentation. Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise. Lots of robust fuzzy C-means algorithms have been proposed in the literature to solve this problem. A general solution is to add the spatial information to the object function of fuzzy C-means. This paper describes the way of embedding the spatial information and shows the advantages and disadvantages of this method.

  Fusion of MultiLevel CenterSymmetric Local Binary Pattern Features

  LU Jianyun，HE Zhongshi，YU Lei

  2010, 32(6): 48-51. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 667 )   PDF (642KB) ( 517 )   　　

  Generally, the centersymmetric local binary pattern (CSLBP) is used to extract features from the  face images only once, by which the extracted texture features are not adequate to represent the face images. Therefore, we employ CSLBP to extract more abundant and informative texture features for more times, and a new face recognition method is proposed which is on the basis of the fusion of multilevel centersymmetric local binary pattern features. In this method, first, the CSLBP is utilized to extract the first level features from the original face image; then, the second level features are extracted from the  feature image by CSLBP again; likewise, we can obtain the multilevel texture features and then fuse different level features to represent face images. The experimental results on the ORL and Yale face databases demonstrate that compared with one level face image features, the method of fusing the  multilevel CSLBP features can improve the face recognition accuracy obviously.

  An Improved Quality Evaluation of Binary Images

  ZHANG Xinhong1，ZHANG Fan2，ZHANG Junliang2

  2010, 32(6): 52-54. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 511 )   PDF (433KB) ( 441 )   　　

  In this paper, we propose a novel distance measure: border distance, and then we propose an objective quality evaluation measure for binary images. Firstly, we get the impact factors of binary images according to the border distance of the modified pixel; then join the impact factors into a mean square error (MSE) and calculate the value BMSE which is based on binary image quality evaluation. Finally, BMSE  is calculated, which is the standardization of BMSE. The experimental results show that the proposed method well matches the subjective apperception of human visual perception.

  Research on the Location of PDF417 Under the Complicated Background

  LIU Fayao，YIN Jianping，LI Kuan，LI Yong

  2010, 32(6): 55-57. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 685 )   PDF (530KB) ( 699 )   　　

  PDF417 is one of the widely used twodimensional barcodes, and the detection and location of its barcode area becomes a critical issue in the recognition process. While the location technique under the complicated background is far more than perfect now.We study this problem in this paper. Based on this, an algorithm based on mathematical morphology operations and the Canny marginal detection is proposed, afterwards, some local precise work is done to achieve the accurate location of the barcode area. The experimental results show that the method can effectively recognize the PDF417 barcode under various complex backgrounds, such as low contradistinction, blurred edges, incline and logo interference.

  Face Recognition Based on the Incremental  Learning Support Vector Machine

  L Junya1,HAN Zhongjun2

  2010, 32(6): 58-60. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 588 )   PDF (431KB) ( 358 )   　　

  To improve the face recognition rate, this paper proposes an incremental learning support vector machine (SVM) face recognition scheme to update the parameters of SVM efficiently. The proposed scheme adopts the Gaussian probability model to depict the parameters of SVM, and updates the parameters of SVM based on the incremental learning SVM without saving the training data. The proposed scheme also employs the rule that minimizes the error of classifications to maximize the distance of the output distributions of two classes. The detailed experimental results and comparisons with the existing schemes show that the proposed scheme can obtain better recognition performance.

  A Method for Extracting Image Semantics of Local Features

  LIU Yi

  2010, 32(6): 61-64. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 488 )   PDF (497KB) ( 567 )   　　

  A method for extracting image semantics of local features is presented based on the Expectation Maximization algorithm(EM). The local image features are first extracted and the visual words in codebook are  used to describe every feature, and then the semantic model mapping from lowlevel image features to highlevel image semantics is achieved by using probabilistic latent semantic analysis. The latent semantic probability distribution is calculated for local features,and their spatial distribution in image is calculated using the ExpectationMaximization algorithm. Finally, this semantic probability distribution is used to image analysis and understanding. Compared to other semanticbased image understanding methods, the proposed method extract local latent semantics directly, which does not require manual annotation. It not only obtains the local semantic information, but also receives the distribution of semantic space. And thus it is better to model the scenes. The experimental results show that this method has satisfactory classification performances on a large set of 15category scenes.

  Ａ Denoising Algorithm for Color Images Based on the Second Generation Bandelet Transform

  YANG Juyi

  2010, 32(6): 68-67. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 595 )   PDF (403KB) ( 433 )   　　

  In this paper，we propose a color image denoising algorithm based on the second generation Bandelet transform to aim at the latest development of the characteristics of the Bandelet transform. The algorithm takes full advantage of the inherent geometry regularity of color images, gets the optimization expression, sets the threshold using noise intensity, and realizes color image denoising using the softthreshold function. The experimental results in the MATLAB tool show that the color image processed by this algorithm improves more effectively than wavelet and the first generation Bandelet algorithm both in subjective visual and objective quality targets.

  An Approach to the Automated Integration of MultiAgent Systems Based on TwoWay Selections

  FANG Xi,MA Jianzhu,WANG Maoguang,JIAO Wenpin

  2010, 32(6): 68-73. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 628 )   PDF (588KB) ( 321 )   　　

  The integration process can have a significant effect on the performance of MutiAgent systems (MAS). At present, most of the integration approaches of MAS focus on the behaviour and performance at the system level. In this paper, we are concerned about the performance of multiagent systems as well as the revenues of individual agents. This paper presents an approach to the integration of multiagent systems based on twoway selections. In the approach, agents apply for the roles accroding to their capabilities and how well the  roles meet their desires, while the  roles choose agents based on how well the agents fulfill tasks. In the process of twoway selections, the roles will evaluate the degree of trustworthiness of the agents dynamically and adjust the trust degrees in time. Experiments show the performance of multiagent systems can improve rapidly and the revenues of agents can gradually increase in a given interval.

  Dynamics Analysis of the MultiAgent  Social Evolutionary Algorithm

  PAN Xiaoying

  2010, 32(6): 74-76. doi: 10.3969/j.issn.1007130X.2010.

  Abstract ( 533 )   PDF (393KB) ( 420 )   　　

  With a typical and simple 2bit problem, the global dynamic shape of the multiagent social evolutionary algorithm is comprehensively analyzed in this paper. The common evolution operators and their combinations are also formally described. Furthermore, a mathematical model is established based on the simplified MASEA. The effect that every evolutionary operator has on the dynamic shape is discovered by the attraction analysis of the fixed points in the models. The global convergence of MASEA is also proved for the 2bit problem.