Table of Content

01 July 2012, Volume 32 Issue 07

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Network and communications

Location error eliminating approach for network delay measurement based on network driver interface specification

CHEN Shi-qiang ZHOU Xu WANG Jun-Feng TANG Hui

2012, 32(07):  1787-1790.  DOI: 10.3724/SP.J.1087.2012.01787

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In the network performance measurement, location error is one of the main factors which influence the accurate network delay measurement. To reduce location error, an improved method for delay measurement was proposed based on Windows Network Driver Interface Specification (NDIS). By using this method, the timestamp position was removed from application to NDIS Intermediate Driver (ID) which was embedded between Miniport Driver (MD) and Protocol Driver (PD), and then the measurement program could calculate the network delay according to those timestamps. Compared with the traditional method, the experimental results show that the proposed method can nearly eliminate location error, and make sure the measurement standard deviation to be lowered than 10μs under different packet-lengths and host-loads. The improved measurement method does not need additional software and hardware, so it has lower measurement cost and can be applied widely.

Hybrid optimization packet scheduling algorithm for CICQ switches

GAO Zhi-Jiang ZENG Hua-shen SHEN Zhi-Jun

2012, 32(07):  1791-1795.  DOI: 10.3724/SP.J.1087.2012.01791

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Combined Input-Crosspoint-Queued (CICQ) Crossbar outperforms traditional switch fabrics. In this paper, the features of CICQ switches were discussed and a new scheduling algorithm called Hybrid Optimization Packet Scheduling (HOPS) was proposed. This algorithm was based on a hybrid optimization method. The throughput of the algorithm was guaranteed in the first stage of input scheduling and the delay performance was improved by serving the longer queue in the second stage. HOPS was mainly based on Round-Robin (RR) mechanism and at most one comparison operation was done at input port, so it had a complexity of O(1) and easy to implement in hardware. With fluid model techniques, it was proved that HOPS algorithm can achieve 100% throughput for any admissible traffic without using speed-up. The simulation results show that HOPS algorithm exhibits favorable delay, throughput performance and stability under any admissible traffic.

New effectiveness evaluation indicator for network node

DUAN Mo-yi

2012, 32(07):  1796-1798.  DOI: 10.3724/SP.J.1087.2012.01796

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To mitigate the network congestion by node failures, a new effectiveness evaluation method was proposed with reference to wavelet transform. In this method, the long-range dependence of actual traffic was depicted at first, and the prediction algorithm of arrival traffic was established with Auto-Regressive and Moving Average (ARMA) model, of which standard deviation between the prediction data and actual data was 6.89. Then, a simulation was conducted to research the relationship between the effectiveness and other influential factors. The results show that the effectiveness is of positive correlation with average velocity, and negative correlation with buffer size.

Resources searching method for unstructured peer-to-peer networks based on shortcuts between subtrees

WU Xiao-Jun CHEN Ji FANG Pei GUO Hai-liang

2012, 32(07):  1799-1803.  DOI: 10.3724/SP.J.1087.2012.01799

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Through studying resources searching methods of unstructured Peer-to-Peer (P2P) network, a new P2P overlay network was proposed. Using a multi-way balanced tree topology, the network created shortcuts between the added node and each subtree of the root when a new node inserted, which forwarded first-hop of a query message only, and then query messages could be forwarded in parallel in each subtree of the root without relying on the root. Compared with the performance of Gnutella and Random Walks network in simulation, the proposed network had lower messages redundancy ratio, higher resource searching success ratio and lower average searching time complexity. The analytical results show that the proposed network is efficient and feasible for searching resources.

New limited feedback method with lower overhead in MIMO-OFDM system

LI Yan JING Xiao-rong YU Xiu-lan ZHANG Zu-fan CHEN Qian-bin

2012, 32(07):  1804-1806.  DOI: 10.3724/SP.J.1087.2012.01804

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This paper investigated the limited feedback technology based on the Multiple Input Multiple Output Orthogonal Frequency Division Multiple (MIMO-OFDM) system in LTE-Advanced applications. A new limited feedback method based on recursive feedback was proposed. The method utilized the correlation between the subcarrier channels. The codewords for the current subcarrier could be determined by ordering the result of the inner product with respect to the codewords of the previous subcarrier. Then the variable length encoding method was used to code the index of the new codewords. The experimental results show that the recursive feedback algorithm based on variable length coding can reduce the feedback bits effectively in LTE-Advanced systems.

Traffic identification based on transport-layer topology at network aggregation point

ZHANG Jian CAO Ping SHOU Guo-chu

2012, 32(07):  1807-1811.  DOI: 10.3724/SP.J.1087.2012.01807

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Considering the complexity and poor real-time quality of classification algorithms based on the statistical characteristics of network traffic, a new traffic identification method was proposed based on transport-layer topology. According to the different host connection characteristics in terms of application types at aggregation point, the proposed method extracted topological characteristics of application types by capturing the transport layer connection information, and then produced application type pools based on Deep-in Packet Inspection (DPI) technique, finally identified the application types of traffic combining the pools and heuristic rules. The experimental results show that the proposed method gains precision higher than 85% for identifying main application types and reduces ratio of un-identified flows from 18% to 7%. It utilizes transport-layer topology information of different application types and can enhance the recognition accuracy of application types.

MTRM: real-time monitoring method for multi-protocol label switch traffic engineering tunnel

ZHU Li-na LIANG Wei ZHAO Rui-lian BI Jing-ping

2012, 32(07):  1812-1815.  DOI: 10.3724/SP.J.1087.2012.01812

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The available network management approaches are not able to monitor Multi-protocol Label Switch (MPLS) Traffic Engineering (TE) tunnels dynamically in real-time. To address this problem, a real-time monitoring approach for MPLS TE tunnels, called MPLS TE Tunnels Real-time Monitoring (MTRM), was proposed in this paper. A probe was placed in the network to collect Open Shortest Path First-TE (OSPF-TE) signaling messages passively. Based on the collected information, a MPLS network model was built and tunnel paths were dynamically computed using the tunnel paths real-time monitoring algorithm. The MPLS TE tunnel paths could thus be monitored in real-time. The simulation experiments were carried out on a MPLS network with 15 nodes. The results show that the proposed approach can monitor the changes of MPLS TE tunnels within five seconds, with precision over 90%. This real-time monitoring approach can greatly reduce the difficulties of MPLS network management and TE implementation, and it has a wide application prospect.

Adaptive UDP flow detection based on multi-granularity

LI Ning YIN Hong XU Ji-heng WANG Jian-min CHEN Hong-yue

2012, 32(07):  1816-1819.  DOI: 10.3724/SP.J.1087.2012.01816

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Concerning the lack of research on User Datagram Protocol (UDP) flow detection, and its low accuracy and efficiency, an adaptive UDP flow detection based on multi-granularity was proposed. Two different dynamic timeout strategies based on different granularity were designed by analyzing the characteristics of UDP flow. Compared with other timeout strategies, the accuracy of the proposed method was similar to the fixed timeout strategy, and the memory usage was only about 75% of the others. The experimental results show that the proposed method is suitable to the UDP flow detection.

Compressive sensing for ultra-wideband signals based on multi-band orthogonal frequency division multiplexing

WANG Gao-bin MA She-xiang

2012, 32(07):  1820-1822.  DOI: 10.3724/SP.J.1087.2012.01820

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To resolve the problem of excessively high sampling rate of the Ultra-WideBand (UWB) signals, the authors proposed a Modified Parallel Segmented Compressive Sensing (MPSCS) method. In UWB communication system based on Multi-Band Orthogonal Frequency Division Multiplexing (MB-OFDM), this paper employed reconstruction algorithm based on Orthogonal Matching Pursuit (OMP) of MPSCS for compressive sampling and signal reconstruction. To compare the Bit Error Rate (BER) performance and sampling rate of MPSCS with Parallel Segmented Compressive Sensing (PSCS) and Nyquist method, simulation had been done in CM1 channel. The simulation results demonstrate that MPSCS has the advantages in BER, sampling rate and UWB signal can be accurately reconstructed by using MPSCS when the sampling rate is only 6.06% of Nyquist rate.

Power control algorithm with faster convergence based on non-cooperative game for cognitive radio networks

ZHU Bing-lian YUN Ming-hua QIAN Ming-da ZHANG Lei

2012, 32(07):  1823-1826.  DOI: 10.3724/SP.J.1087.2012.01823

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Concerning the slow convergence of distributed power control algorithm in cognitive radio, a novel algorithm based on non-cooperative game was proposed for cognitive radio system. A Signal-to-Interference Ratio (SIR)-based tangent cost function of fewer iterations was designed to improve the convergence. The simulation results demonstrate that, compared with the Koskie-Gajic algorithm and the Cognitive Radios-Non-Cooperative Power Control Game (CR-NCPCG) algorithm, the proposed algorithm at the premise of satisfying the secondary users' demand for SIR and the primary user's interference temperature constraint, not only can fast converge, but also has higher average SIR with at least 0.3dB when the number of users is less than twenty. It can control the power of secondary users effectively.

Fast clustering scheme of base station group based on partial CSI and uniform cluster size

LI Kun HUANG Kai-zhi LU Guo-ying

2012, 32(07):  1827-1830.  DOI: 10.3724/SP.J.1087.2012.01827

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In the case of Channel State Information (CSI) distortion and channel fast changing, the existing clustering scheme needs to get CSI of all the base stations and generates cluster structure slowly. Concerning the problem, a fast clustering scheme based on Affinity Propagation (AP) algorithm was proposed in this paper. The scheme just needs CSI of neighboring base stations. Firstly, sparse similarity matrix was formed by the average Signal to Interfere Ratio (SIR) of cooperation between neighboring base stations. Then, among neighboring base stations, the interaction and update of collaborative information was done to quickly generate multiple clusters. Finally, the average SIR of cooperation between clusters was normal when the smaller clusters were combined to achieve the purpose of uniform cluster size. The simulation results show that the performance of the proposed scheme is better than the existing scheme in terms of convergence and cluster size uniformity.

Location system design based on wireless sensor network for landslide monitoring

WANG Bo LI Wen-tian MEI Qian

2012, 32(07):  1831-1835.  DOI: 10.3724/SP.J.1087.2012.01831

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To solve such problems as high cost, low automation and not-easy installation of the existing landslide monitoring system, a wireless remote landslide monitoring system was designed. In this system, landslide information was obtained by ZigBee location technology rather than landslide sensors and monitoring data was transmitted by General Packet Radio Service (GPRS) to the data center. Therefore, the landslide could be monitored remotely and automatically. The design plan of the system structure, software and hardware based on the improved Received Signal Strength Indicator (RSSI) location algorithm were introduced. A simulation experiment was done with a result of 1.39m error and 0.5m error fluctuation by OPENT and Matlab in 10m×15m testing area. The research and experimental results show that this system can reduce the cost of landslide monitoring system significantly without any sensors, and it has the properties of low cost, simple implementation procedure and high automation level.

Intelligent algorithm for locating nodes in wireless sensor network based on processing strategy of optimal hopping distances

LI Mu-dong XIONG Wei GUO Long

2012, 32(07):  1836-1839.  DOI: 10.3724/SP.J.1087.2012.01836

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Focusing on the problems of poor locating performance and ignoring anchor nodes' inaccuracy in traditional DV-Hop algorithm which is one of the range-free algorithms in Wireless Sensor Network (WSN), an intelligent algorithm for locating nodes based on Processing Strategy of Optimal Hopping Distances (PSOHD) was proposed. Fully considering the effect of dynamic topology and anchor nodes' difference, this algorithm firstly introduced two communication radii with anchor nodes to calculate the nodes of communication range respectively. Secondly, the average one-hop distance among anchor nodes was refined by means of weighted least squares estimation. Finally, the average one-hop distance used by each locating node for estimating its location was optimized through weighting the N received average one-hop distances from anchor nodes. In addition, Particle Swarm Optimization (PSO) algorithm was presented to locate the unknown nodes. The simulation results show that the improved algorithm has obviously better location precision at the cost of increasing appropriate energy. Thus, it is a practical scheme for WSN with both inaccuracy of anchor nodes and random dynamic topology.

Maximal weighted clustering algorithm based on connected dominating set for MANET

LI Jin PAN Hong LIU Zhong-bing

2012, 32(07):  1840-1843.  DOI: 10.3724/SP.J.1087.2012.01840

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The authors studied the clustering mechanism in Mobile Ad Hoc Network (MANET) and proposed a maximal weighted clustering algorithm based on connected dominating set, including clustering algorithm and clustering maintenance strategy. The comprehensive performance of nodes was quantized by the weighted amount of node mobility, minimum average emissive power, and the energy consumption rate. The improved algorithm for solving connected dominating set was used for clustering the nodes, which made the higher performance nodes be the cluster heads and reduced the number of clusters. The simulation results show that the proposed algorithm is beneficial to improving the load balancing ability and enhancing the robustness and stability of the network.

Modeling and analysis of multiple input multiple output MAC under link quality of service constraints

DENG Xue-bo WANG Xiao-qiang CHEN Xi MA Rui LIAO Yong LI Ping NIU Xiao-jun

2012, 32(07):  1844-1848.  DOI: 10.3724/SP.J.1087.2012.01844

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To solve the insufficiency of Stream Control Multiple Access (SCMA) protocol that it fails to consider both the link Quality of Service (QoS) and the channel access scheduling policy of Multiple Input Multiple Output (MIMO) stream, this paper put forward a SCMA/QA protocol. This protocol fully considered the channel states of different streams in each link and built up a discrete Markov chain model based on channel state of stream. Moreover, it took the request of QoS in each link into consideration and adopted fixed Request to Send/Clear to Send (RTS/CTS) to exchange the information of link QoS and taking the link QoS weight as a primary case in link decision, made the link scheduling problem based on QoS of MIMO modeled as an optimization problem, which led to the result of optimal link and the number of communication streams under the Karush-Kuhn-Tucker (KKT) conditions. Finally, according to the numerical analysis which set throughput as the parameter of the QoS, the results show that under the same network environment the SCMA/QA improves the system throughput much better than SCMA and QoS-aware Cooperation SCMA (QCSCMA).

Handover algorithm combined with location prediction in 3GPP LTE systems

SUN Wei-wei SU Han-song TENG You-wei XU Yong

2012, 32(07):  1849-1851.  DOI: 10.3724/SP.J.1087.2012.01849

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Concerning the problem of the decline of 3GPP Long Term Evolution (LTE) system throughput caused by the frequent handover, a location prediction model based on user movement mechanism and changing probability of direction was proposed. The proposed model was combined with the standard handover algorithm of LTE. The model calculated the weight of each possible location using the changing probability of direction, then got the predicted received signal strength through summing. The simulation results show that the number of handover does not change obviously, but the system throughput is improved after using the combined algorithm. In addition, the proposed model is better than the traditional data mining prediction model.

Transmission technique of hybrid automatic repeat request based on frequency resources re-election in long term evolution

LIU Gao-hua SU Han-song ZHANG Wei

2012, 32(07):  1852-1855.  DOI: 10.3724/SP.J.1087.2012.01852

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Concerning the optimization of resource blocks during the Hybrid Automatic Repeat reQuest (HARQ) process in Long Term Evolution (LTE) system, a new method of data retransmission based on grouping of frequency resources re-election was proposed. The frequency resources were grouped according to the used bandwidth, and the introduction of group number judgement and frequency resource block selection could obtain higher diversity gain. With the constructed HARQ model incorporating Incremental Redundancy (IR) and Chase combining technique, the simulation results indicate that the improved method can enhance the Block Error Ratio (BLER) performance with 1.2dB in poor channel condition and reduce the average number of retransmission.

Graphics and image technology

Fast disparity estimation algorithm based on features of disparity vector

SONG Xiao-wei YANG Lei LIU Zhong LIAO Liang

2012, 32(07):  1856-1859.  DOI: 10.3724/SP.J.1087.2012.01856

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Disparity estimation is a key technology for stereo video compression. Considering the disadvantage of the epipolar correction algorithm, a fast disparity estimation algorithm based on the features of disparity vector was proposed. The algorithm analyzed the features of disparity vector in parallel camera and convergent camera systems respectively, and explained how to find the best matching block by a three-step search according to their features. The algorithm was tested in both 640×480 and 1280×720 resolution sequences. The experimental results show that compared to the original TZSearch algorithm in JMVC, the proposed algorithm can effectively shorten the encoding time and improve coding efficiency without decreasing the image quality and compression efficiency. Because there is not epipolar correction in the proposed algorithm, the disadvantage caused by epipolar correction will not appear.

Shadow generation algorithm of augmented reality using adaptive sampling and fusion

LI Hong-bo WU Liang-liang WU Yu

2012, 32(07):  1860-1863.  DOI: 10.3724/SP.J.1087.2012.01860

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Since the soft shadow achieved by the existing shadow generation algorithms of Augmented Reality (AR) is unrealistic, the authors proposed a shadow generation algorithm using adaptive sampling and background fusion. First, the authors computed shadow spatial location distribution of virtual objects by using planar shadow algorithm which took occlusion into account. Then, to improve the procedure of soft shadow generation in swell and erode algorithm, an adaptive sampling method which got illuminant union according to shape types was presented. Finally, since shadow color gotten by gray image method was limited to single channel, the authors presented a method based on multi-channel and background fusion. The experimental results show that in the proposed algorithm the color of soft shadow is more reasonable and the method of soft shadow rendering is more effective. Consequently, the presented algorithm improves the realism of soft shadow.

Improved fast new edge-directed fractional interpolation algorithm

LIU Nan BI Du-yan LIN Jia-hao YANG Zhong-bin

2012, 32(07):  1864-1867.  DOI: 10.3724/SP.J.1087.2012.01864

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The original New Edge-Directed Interpolation (NEDI) algorithm is of high complexity, difficult for hardware implementation, and the interpolated images may suffer from blurring edges around edge area. To achieve a better subjective quality, an improved NEDI algorithm was proposed in this paper. In the new algorithm, a circular window was adopted, and the interpolation coefficient calculation was calculated only once, which could be reused in interpolating the center-pixels, thus the errors introduced by iterative computation were avoided and the interpolation time was saved. As to non-center pixels, six original neighbors were involved to estimate local covariance characteristics at high resolution. In comparison with the results of bi-cubic interpolation and the traditional NEDI, the experimental results indicate that proposed algorithm can eliminate the sawtooth of the interpolated picture in large-scale, and decrease the computational complexity.

Quartic Hermite interpolating splines with parameters

LI Jun-cheng LIU Chun-ying YANG Lian

2012, 32(07):  1868-1870.  DOI: 10.3724/SP.J.1087.2012.01868

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To overcome the defects of the standard cubic Hermite interpolating splines, a class of quartic Hermite interpolating splines with parameters was presented in this paper, which inherited the same properties of the standard cubic Hermite interpolating splines. Given the set interpolating conditions, the shape of the proposed splines could be adjusted by changing the values of the parameters. If the parameters were chosen properly, the quartic Hermite interpolating splines could achieve C2 continuity and approximate to the interpolated functions better than the standard cubic Hermite interpolating splines. The proposed new splines further enriched the theories of Hermite interpolating splines, and provided a new method for constructing interpolation curves and surfaces.

Millimeter wave image restoration based on fuzzy radial basis function neural networks and sparse representation

SHANG Li SU Pin-gang CHEN Jie

2012, 32(07):  1871-1874.  DOI: 10.3724/SP.J.1087.2012.01871

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As to the problems that Millimeter Wave (MMW) image is contaminated by much unknown noise and has lower resolution, and considering the non-linear filter property of Fuzzy Radial Basis Function Neural Network (F-RBFNN) and the self-adaptive denoising property of Sparse Representation (SR) based on K-Singular Value Decomposition (K-SVD), a MMW restoration method was proposed by combining F-RBFNN and sparse representation. In F-RBFNN, the knowledge expression of fuzzy logic and the reasoning ability were combined with the RBFNN's capabilities of fast learning and generalization. In order to realize the non-linear filtering to the MMW image, F-RBFNN's structure and parameters were adjusted according to the real problem. Furthermore, utilizing the advantages of sparse representation method, which the sparse representation behaves the visual characteristic and can denoise effectively when maintaining features of the object, the training results of F-RBFNN were locally denoised once again, and the MMW image with high resolution was obtained. Using the Relative Single Noise Ratio (RSNR) criterion to measure the quality of denoised images, the simulation results show that, compared with other denoising methods such as F-RBFNN, K-SVD denoising, and wavelet denoising, the proposed method combining F-RBFNN and SR can better restore the quality of MMW image.

New method of blurred radius detection in defocused image

2012, 32(07):  1875-1878.  DOI: 10.3724/SP.J.1087.2012.01875

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An algorithm combining local entropy and histogram statistics was proposed in order to solve the problem that it is difficult to detect the blurred radius quickly and correctly in defocused image blind restoration. Firstly, the gray level information of blurred image was extracted by local entropy filter and straight lines were detected by Canny edge detector and Hough transform. Secondly, the straight step edges were located to compute the line spread function adopting Grubbs method and histogram feature of the parallel line area. Finally, the blurred radius could be obtained by line spread function. The experimental results show that the step edges can be located quickly and accurately when blurred radius is small, thus increasing recognition accuracy and recognition efficiency.

Improved variational model to remove multiplicative noise based on partial differential equation

HU Xue-gang ZHANG Long-tao JIANG Wei

2012, 32(07):  1879-1881.  DOI: 10.3724/SP.J.1087.2012.01879

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In this paper, a new variational model based on Partial Differential Equation (PDE) was proposed to solve the ill-posed problems in the data-fidelity item of the existing key variational approaches to remove multiplicative noise with the theories of total variation and logarithmic transformation. The initial boundary value problem of the PDE associated with the new variational problem was derived and discreted numerically. The numerical experimental results show that the values of Mean Square Error (MSE) are decreased and Peak Signal to Noise Ratio (PSNR) are increased obviously. The ill-posed problem in the data-fidelity item is avoided well at the same time. It makes a good method to solve this problem, and avoids the errors which may appear in the discretization process. The quality of the images restored by the proposed method is not only more favorable, but the new model also eliminates the “step-casing effect”.

Method of image visual quality evaluation based on human visual characteristics

HU Xu-ming ZHANG Deng-fu NAN Dong CHEN Diao

2012, 32(07):  1882-1884.  DOI: 10.3724/SP.J.1087.2012.01882

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To better evaluate image quality, the authors proposed a top-down no-reference image objective quality evaluation method based on the research of human visual model and human visual characteristics. The new method divided the target image into segments and calculated every segment in different color channel, then output the average visual property values. It made evaluation model not only be consistent with the advantage of objective quality assessment, but also took into account the human visual experience. It was consistent with the objectivity and subjectivity of human eyes. The validated results of image subjective evaluation on database of TEXAS University of United States prove that the proposed method gets better consistency with subjective assessment.

Effective detection algorithm based on two-threshold and iteration for images with impulse noise

YANG Run-ling ZHOU Jun-ni WEI Rui

2012, 32(07):  1885-1889.  DOI: 10.3724/SP.J.1087.2012.01885

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An effective noise detection algorithm based on two-threshold and iteration for noise images with impulse noise was proposed to decrease the influence of impulse noise. The selective method of two-threshold was reliable in theory, and the two-step iteration method guaranteed the accuracy of noise detection. Moreover, the median filtering algorithm with selected pixels made sure that the details of image were not blurred at the same time. The experimental results show that the proposed algorithm is more robust and adaptive, and it has lower leak-detection and better filtering effect.

Face recognition using nonsubsampled Contourlet transform and local binary pattern

YUE Xu-yao YANG Hui-xian ZHU Gui LENG Ai-lian LI Li

2012, 32(07):  1890-1893.  DOI: 10.3724/SP.J.1087.2012.01890

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Concerning the problem of limited recognition rate caused by variations in position, illumination and expression in face recognition, an efficient face recognition method based on Nonsubsampled Contourlet Transform (NSCT) and Local Binary Pattern (LBP) was proposed. Firstly, a face image was decomposed with NSCT, and NSCT coefficients in different scales and various orientations were obtained; LBP operator was then used to get LBP feature maps by extracting local neighboring relationship from NSCT coefficients; Finally, feature maps were respectively divided into several blocks, the concatenated histograms, which were calculated over each block, were used as the face features. The experimental results using multi-channel nearest neighbor classifier based on Euclidean distance show that, the proposed method can improve the recognition rate effectively, and the extracted feature is robust to variations of illumination, face expression and position.

Study on dimensionless dynamic characteristics of flame based on image recognition

HUANG Zheng-yu MIAO Xiao-ping RUI Ting

2012, 32(07):  1894-1898.  DOI: 10.3724/SP.J.1087.2012.01894

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Concerning the difficulty in consistent description of flame dynamic characteristics, a dimensionless detection method was proposed. A "search" method was made to segment the suspicious districts. Then three dynamic dimensionless characteristic factors were extracted to train a Bayesian classifier after analyzing the characteristics of flame and the final detection result was realized. Of all three characteristic factors, the "flame dynamic constant" factor has "stable" characteristics and its statistical values range from -0.003 to 0.003. It has broken the spatio-temporal restriction of traditional research and is free from the influence of the flame development stages, space-scales of detection and varieties of surveillance devices. Under the flame detection experiments on different distance sequences of 200 frames, the correct recognition rate based on dimensionless features, compared with the general features, was almost over 90%. The experimental results show that the proposed factors are better able to describe the flame characteristics and they can greatly improve the efficiency of flame detection and boost the robustness of fire detection system.

Automatic extraction of feather quill based on Normalized cut algorithm

YUE Hong-wei WANG Ren-huang HE Zui-hong

2012, 32(07):  1899-1901.  DOI: 10.3724/SP.J.1087.2012.01899

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A modified Normalized cut (Ncut) method considering the texture weight was proposed to effectively segment feather quill. The weight including texture information enhanced association on each edge of similar texture and reduced interference of the similar region. Narrow unidirectional expansion method with a region-scalable fitting term was used to optimize the initial boundary for the final result and eliminated boundary leakage of the feather quill. The experimental results show that the proposed method can realize boundary extraction of feather quill efficiently and pave the way for the next step research of crease detection.

Endocardium and epicardium segmentation of left ventricle in cardiac magnetic resonance images based on directional Snake model

ZHANG Ning YU Xue-fei LU Guang-wen

2012, 32(07):  1902-1905.  DOI: 10.3724/SP.J.1087.2012.01902

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Concerning that the edges of the endocardium and epicardium of the left ventricle in the cardiac Magnetic Resonance Imaging (MRI) images have different directions, a new directional active contour model in curve evolution framework was proposed for segmentation of endocardium and epicardium of the left ventricle. The curve evolution equation included a hybrid geometric flow with edge and region gray characteristics that were obtained from the image itself. The edge-based term in the geometric flow borrowed from extended Dynamic Directional Gradient Vector Flow (DDGVF) with fast marching method was utilized to guide the curve evolution towards the object boundaries with different direction. The region-based term borrowed from Chan-Vese (CV) model was utilized to prevent the curve from leakage under the influence of other edge components. The final curve evolution equation was dealt with level set method. The experimental results for gray and cardiac MRI images show that the proposed method can get better segmentation effects. It has certain application value for realizing myocardium auto-segmentation, evaluation and analysis of heart function based on cardiac MRI images.

Recognition approach for ballot symbol based on run features

ZHANG Jing-jin XIAO Gang ZHANG Yuan-ming LU Jia-wei XU Jun

2012, 32(07):  1906-1909.  DOI: 10.3724/SP.J.1087.2012.01906

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Recognition of hand-written ballot symbols is crucial in vote-counting system based on image understanding. To improve the accuracy of ballot symbol recognition, a symbol recognition approach based on run feature was proposed. Firstly, the concept of run was presented and a discriminant model was established based on run features of ballot symbols. Secondly, the relative positions of runs were described with a ternary tree. In addition, the main run regions were extracted in noisy environment by merging run regions, and an approach of recognizing ambiguous symbols was also given. Finally, the experimental results show that the run features can accurately reflect the geometrical features of ballot symbols. The proposed approach achieves high accuracy, and its accuracy is 6.07% higher than that of template matching algorithm.

Network and distributed techno

DPST: a scheduling algorithm of preventing slow task thrashing in heterogeneous environment

DUAN Han-cong LI Jun-jie CHEN Cheng LI Lin

2012, 32(07):  1910-1912.  DOI: 10.3724/SP.J.1087.2012.01910

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With regard to the thrashing problem of load-balancing algorithm in heterogeneous environments, a new scheduling algorithm called Dynamic Predetermination of Slow Task (DPST) was designed to reduce the probability in slow task scheduling and improve load-balancing. Through defining capability measure of heterogeneous task in heterogeneous nodes, the capacity of nodes which performed heterogeneous tasks was normalized. With the introduction of predetermination, thrashing result from heterogeneous environments was reduced. By using double queues of slow task and slow node, the efficiency of scheduling was improved. The experimental results show that the thrashing times in heterogeneous environments fell by more than 40% compared with Hadoop. Because thrashing times have been reduced effectively, DPST algorithm has better performance in reducing average response time and increasing system throughput in heterogeneous environments.

Power-aware resource scheduling under cloud computing environment

XU Jun-yong PAN Yu LING Chen

2012, 32(07):  1913-1915.  DOI: 10.3724/SP.J.1087.2012.01913

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Under the cloud computing environment, it has become a significant problem to decrease the power consumption while the makespan is shortened in the process of scheduling resource. Thus, this paper made span and power consumption as the optimization objectives and established power-aware resource scheduling model, then improved the Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) by adopting special initialization and the learning algorithm, to solve the problem of power-aware scheduling. Consequently, the simulation results prove that the proposed scheduling algorithm not only shortens the makespan, but also decreases the power consumption effectively.

Multi-objective integrated ant colony optimization scheduling algorithm based on cloud resource

ZUO Li-yun ZUO Li-feng

2012, 32(07):  1916-1919.  DOI: 10.3724/SP.J.1087.2012.01916

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With regard to the complexity of cloud computing and uncertainty of cloud resources, an integrated multi-objective ant colony optimization scheduling algorithm was proposed. Using entropy to measure the uncertainty of cloud resources, and updating the global pheromone, the algorithm's convergence rate could be improved. In order to achieve the minimum activation time, the expected minimum completion time calculated by Min-min algorithm was used as heuristic information. When the local pheromone was updated partly, the load factor was added according to the current load regulation of pheromone, to achieve the load balance. Collaboration between ants could be enhanced and the performance of the optimal solution would be improved, considering the pheromone diffusion factors, that is to consider not only the current node pheromone but also neighbor node pheromone. The advanced ant colony algorithm reduced the complexity of the algorithm better than the original algorithm, and improved the optimal solution accuracy. The experiments of the cloud simulation system prove that the performance of time scheduling and load balancing of the proposed algorithm is better than other algorithms.

HBase-based storage system for large-scale data in wireless sensor network

CHEN Qing-kui ZHOU Li-zhen

2012, 32(07):  1920-1923.  DOI: 10.3724/SP.J.1087.2012.01920

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Wireless Sensor Network (WSN) spreads widely, and with the expansion of WSNs there will be a large number of sensors which produce massive sensor data. To store the data from large-scale WSNs, this paper proposed a two-tier storage architecture based on HBase storing sensor data from different regions and global data management directory, which achieved a near real-time storage system. The experimental results show that this system with high scalability, storage and query efficiency can solve the massive sensor data storage.

Cloud storage-oriented unstructured data storage

XIE Hua-cheng CHEN Xiang-dong

2012, 32(07):  1924-1928.  DOI: 10.3724/SP.J.1087.2012.01924

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With the explosive growth of unstructured data, the existing storage technology in the aspects of I/O throughput, scalability and manageability needs improving urgently. Based on cloud storage and reliability theory, a model of distributed storage for unstructured data was created, and reliability function was also proposed. The distributed Relational Database Management System (RDBMS) was adopted as the bottom storage facilities, so unstructured data could be stored directly in the data table. Separated storage and unified management for unstructured data and metadata was realized, and thus storage system performance was promoted. Relative to the centralized storage, new system has superior availability. The simulation results show that the storage system has higher reliability and it is easy to expand. The distributed storage system can be applied to dynamic open computing environment, and it provides cloud storage service with better performance.

Live migration model of virtual machine adapting to wide area network

XU Zhi-hong LIU Jin-jun ZHAO Sheng-hui

2012, 32(07):  1929-1931.  DOI: 10.3724/SP.J.1087.2012.01929

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Concerning the Virtual Machine (VM) migration problems in Wide Area Network (WAN), a live migration model was proposed. The link state between nodes was continuously detected, and the migration time of disk, memory, CPU status and network were optimized. The disk cycle synchronization, unidirectional tunnel and virtual machine localization were implemented. The experimental results show that the model reduces amount of migration data and shortens redirection path in WAN. The total time and pause time are close to the manner of shared storage under simulated conditions.

Particle swarm optimization algorithm with self-adaptive parameter and chaos search for solving flexible job shop scheduling problem

LI Li

2012, 32(07):  1932-1934.  DOI: 10.3724/SP.J.1087.2012.01932

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According to the shortcomings of traditional Particle Swarm Optimization (PSO) algorithm in solving flexible job-shop scheduling problem, this paper proposed particle swarm optimization algorithm with self-adaptive parameters and chaos search. According to the self-adaptive method of parameters such as inertia coefficient based on iteration, particles searched in large scale with high inertia at early time and then got into fine search by reducing inertia. This method solved the problem of blind randomness and low accuracy in traditional particle swarm algorithm. Introduction of chaos technology into local search could expand the search scale for optimization solution and reduce the possibility of falling into local extremum. This method could effectively improve global optimization ability of the algorithm. The experimental results show that the particle swarm optimization algorithm with self-adaptive parameters and chaos search can get more optimal average particle fitness and better optimization objective. The proposed algorithm is feasible and effective for Flexible Job-shop Scheduling Problem (FJSP).

Quantum artificial bee colony optimization algorithm based on Bloch coordinates of quantum bit

YI Zheng-jun HE Rong-hua HOU Kun

2012, 32(07):  1935-1938.  DOI: 10.3724/SP.J.1087.2012.01935

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To solve the problems of slow convergence speed and easily getting into local optimal value for Artificial Bee Colony (ABC) algorithm, a new quantum optimization algorithm was proposed by combining quantum theory and artificial colony algorithm. This algorithm expanded the quantity of the global optimal solution and improved the probability of achieving the global optimal solution by using Bloch coordinates of quantum bit encoding food sources in the artificial colony algorithm; then food sources were updated by quantum rotation gate. This paper put forward a new method for determining the relationship between the two rotation phases in the quantum rotation gate. When the ABC algorithm searched as the equal area on the Bloch sphere, it was proved that the size of the two rotation phases in the quantum rotation gate approximated to the inverse proportion. This avoided blind arbitrary rotation and made the search regular when approaching the optimal solutions. The experiments of two typical optimization issues show that the algorithm is superior to the common Quantum Artificial Bee Colony (QABC) and the simple ABC in both search capability and optimization efficiency.

Photon mapping parallel algorithm based on graphic processing unit

HE Huai-qing SUN Xi-dong

2012, 32(07):  1939-1942.  DOI: 10.3724/SP.J.1087.2012.01939

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To solve the slow rendering speed issue of serial photon mapping algorithm, the feasibility of parallelizing the algorithm was analyzed. The parallelism and computing capability of the Compute Unified Device Architecture (CUDA) on Graphic Processing Unit (GPU) were fully utilized to realize a parallel photon mapping algorithm. As for the shortage of generating the same number of GPU threads as the photon number in the photon emission and tracing step, and the waste of resources of the average allocation method, a new cooperation way that all the threads be processed with dynamic balance was then proposed. The new method nearly doubled the rendering speed. The experimental results prove the effectiveness of the proposed method.

Programming algorithm for reference of discrete dynamic Bayesian network

SHI Jian-guo GAO Xiao-guang

2012, 32(07):  1943-1946.  DOI: 10.3724/SP.J.1087.2012.01943

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The discrete dynamic Bayesian network is a useful tool for modeling and inferring the time series progress, and it has wide modeling application value. But its inference algorithm needs improving. Concerning the shortcomings of the discrete dynamic Bayesian network, such as its inference algorithm is hard to understand, hard to program and running slowly, this paper proposed the most suitable storage data structure of the discrete dynamic Bayesian network, deduced the fast inference algorithm for the discrete dynamic Bayesian network, and verified the inference algorithm for the discrete dynamic Bayesian networks through a sample.

Artificial intelligence

Backtracking clonal selection algorithm for multi-modal function optimization

ZHANG Ying-jie MAO Ci-ping

2012, 32(07):  1947-1950.  DOI: 10.3724/SP.J.1087.2012.01947

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To solve some existing problems in multi-modal function optimization, an improved Clonal Selection Algorithm (CSA) based on the backtracking mechanism, Backtracking Clonal Selection Algorithm (BCSA), was proposed in this paper. The global search capability could be enhanced by using the improved backtracking mechanism and the restraining operation of memory antibodies, which maintained the diversity of antibodies. In addition, in order to improve the convergence speed, the improved dynamic mutation, selection and crossover operation were adopted. The results tested on typical multi-modal functions show that BCSA has a powerful performance in global search.

Particle swarm optimization algorithm based on chaos cloud model

ZHANG Chao-long YU Chun-ri JIANG Shan-he LIU Quan-jin WU Wen-jin LI Yan-mei

2012, 32(07):  1951-1954.  DOI: 10.3724/SP.J.1087.2012.01951

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To deal with the problems of low accuracy and local convergence in conventional Particle Swarm Optimization (PSO) algorithm, the chaos algorithm and cloud model algorithm were introduced into the evolutionary process of PSO algorithm and the chaos cloud model particle swarm optimization (CCMPSO) algorithm was proposed. The particles were divided into excellent particles and normal particles when CCMPSO was in convergent status. To search the global optimum location, the cloud model algorithm as well as excellent particles was applied to local refinement in convergent area, meanwhile chaos algorithm and normal particles were used to global optimization in the outside space of convergent area. The convergence of CCMPSO was analyzed by eigenvalue method. The simulation results prove the CCMPSO has better optimization performance than other main PSO algorithms.

Improved approach of hybrid formation for multi-mobile robots

ZHANG Han-dong HUANG li CEN Yu-wan

2012, 32(07):  1955-1957.  DOI: 10.3724/SP.J.1087.2012.01955

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In a complex environment and concerning the problems of choosing parameters brought by the mixture of two multi-robot formation methods, the Leader-Follower method and a behavior-based method, this paper improved two methods and optimized five kinds of behavior parameters online to make the multi-robot formation better with the help of Particle Swarm Optimization (PSO) algorithm. The simulation results validate that the proposed algorithm is feasible and it achieves expected optimization effects.

Multi-population invasive weed optimization algorithm based on chaotic sequence

CHEN Huan ZHOU Yong-quan ZHAO Guang-wei

2012, 32(07):  1958-1961.  DOI: 10.3724/SP.J.1087.2012.01958

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Concerning the premature convergence of invasive weed optimization algorithm, a new invasive weed optimization with multi-population based on chaotic sequence (CMIWO) was proposed. Firstly, chaotic sequence was adopted to initialize population at the initialization of algorithm, which improved the quality of the initial solution. Secondly, threshold was used to estimate the cluster degree of individuals in iterations and if cluster degree was less than threshold, initializing population with chaotic sequence was implemented again, thus the algorithm could effectively jump out of local minima. Thirdly, the weed population was divided into five groups to collaborate so as to discourage premature convergence, thus improving the algorithm's precision and increasing the convergence speed. In the end, the test results on eight test functions show that the proposed algorithm improves the accuracy by 25% to 300% than basic algorithm in terms of optimal value and 50% to 100% for standard deviation.

Modified self-organizing map network for Euclidean travelling salesman problem

ZHOU Xiao-meng, XU Xiao-ming

2012, 32(07):  1962-1964.  DOI: 10.3724/SP.J.1087.2012.01962

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The Self-Organizing Map (SOM) was modified in this paper: the number of the neurons did not change with time and the neurons collectively maintained their mean to be the mean of the data point in the training phase. After training, every city was associated with a label of a neuron. Then there may be a problem that one or more than one cities have the same neuron. In order to avoid that, a dot labels index was adopted instead of the integer index. The virtue of this scheme is that different city has different index. Then the label would contribute to make sure the order of the city in the tour. Then the algorithm was applied to solve problems taken from a Traveling Salesman Problem Library (TSPLIB). The experimental results show that the proposed algorithm is feasible and effective.

Lotka-Volterra recurrent neural network model for solving shortest path

ZHENG Bo-chuan SANG Yong-sheng

2012, 32(07):  1965-1968.  DOI: 10.3724/SP.J.1087.2012.01965

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The Shortest Path (SP) problem of the directed graph is an optimization problem. By constructing the energy function for the shortest path problem of the directed graph, a Lotka-Volterra (LV) Recurrent Neural Network (RNN) model was proposed to solve the shortest path problem of the directed graph. When the LV RNN converged to its stable attractor, the corresponding energy function also reached its energy minimum point. Therefore, the shortest path of the directed graph could be obtained through the stable attractor of the LV RNN. The experimental results verify that the shortest path between any two vertices in the directed graph can be obtained efficiently by using the LV RNN model.

Design of evaluation-function for computer gobang game system

ZHANG Ming-liang WU Jun LI Fan-zhang

2012, 32(07):  1969-1972.  DOI: 10.3724/SP.J.1087.2012.01969

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Concerning the speed bottleneck of the gobang machine game when relying on the configuration of the stones to evaluate the game states, this paper proposed a multi-layer evaluation-function method combining identification granularity of the stones' configuration with the search depth. The experimental results have proved: the overall efficiency of coarse-grained evaluation was higher when the deep-layer searches were processing; multi-layer judging for the configuration of the stones could obviously accelerate the evaluation; if the move-generating functions were introduced into the rapid evaluation, it was more efficient to prune certain branches from game-tree in advance; gobang game tree searches also benefited if floating the values of non-critical stone's configuration to balance the search depth. Therefore, dynamic evaluation of evaluation-function is more reasonable.

New K-medoids clustering algorithm based on granular computing

MA Qing XIE Juan-ying

2012, 32(07):  1973-1977.  DOI: 10.3724/SP.J.1087.2012.01973

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Traditional K-medoids clustering algorithm has some drawbacks, such as its clustering results being sensitive to initial cluster centers and its deficiency in large datasets. Although the fast K-medoids algorithm overcame the shortcomings of traditional K-medoids, it has the potential disadvantages of selecting the exemplars in the same cluster as initial seeds for different clusters. To overcome the shortcomings of the traditional K-medoids and the fast K-medoids clustering algorithms, a granular computing based K-medoids clustering algorithm was proposed in this paper. The algorithm defined a new similarity function between samples via pooling granularity, where the granules were produced via the equivalence relationship. The density of a granule was defined according to the number of samples in it, after that the K samples closest to the centers of the first K granules were selected as the initial centers for K-medoids clustering algorithm to cluster datasets. The experimental results on the datasets from UCI machine learning repository and on the synthetic datasets all demonstrate that the new granular computing based K-medoids clustering algorithm can find much better initial centers. Its clustering accuracy and its clustering error are better than those of the traditional K-medoids and the fast K-medoids clustering algorithms. It can get much more stable results and can be applied to cluster large datasets.

Fuzzy clustering algorithm based on w-mean distance

ZHANG Rui-li ZHANG Ji-fu

2012, 32(07):  1978-1982.  DOI: 10.3724/SP.J.1087.2012.01978

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In this paper, a fuzzy clustering algorithm based on w-mean distance was proposed to solve such defects of Fuzzy C-Means (FCM) algorithm as easily falling into local optimal value and being sensitive to clustering center and noise data. First, initial clustering centers were determined by making use of the idea of the mean distance according to the distribution of data set, and the regulating factor w was introduced to adjust the mean distance. Second, each sample in data set was assigned a weight, and the clustering center formula and target function formula were modified by the weight, so that the anti-noise performance was greatly improved for the algorithm. In the end, the experimental results validate that the proposed algorithm has good effects on selecting initial clustering centers, avoiding local convergence, and having higher performance of anti-noise and effectiveness.

Meta-association Rule Mining Method for Dynamic Association Rules Based on WMeta-rule mining method for dynamic association rules based on wavelet transformavelet Transform

ZHANG Zhong-lin XU Fan

2012, 32(07):  1983-1986.  DOI: 10.3724/SP.J.1087.2012.01983

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Concerning the problem that the forecast accuracy of the meta-rule mining in dynamic association rules is not high, this paper put forward a method for applying wavelet transform to meta-rule mining in dynamic association rules to improve the forecast accuracy of the rules. Firstly, the Daubechies wavelet was used to transform the support count of the dynamic meta-association rules. Secondly, the approximate part and detailed part could be extracted according to the multi-resolution characteristics of wavelet transform. And then the curve error calculation and selection control of wavelet decomposition level could be processed by using the two parts followed by inverse transforming and curve fitting by using the filtered approximate signal to conduct the predictions. The experimental results prove that the forecast precision is more than 90% by using the last forecast data. Finally, it turns out that the proposed method can better reflect the dynamic information and trends of the rules changing with time so as to get more accurate results of dynamic association rules with the guidance of reasonable meta-rules.

New variant of ISOMAP for imperfect manifold

SHAO Chao ZHANG Hui-juan

2012, 32(07):  1987-1990.  DOI: 10.3724/SP.J.1087.2012.01987

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Isometric Feature Mapping (ISOMAP) requires that the data belong to a single well-sampled manifold; however, when the data are sampled from an imperfect manifold, ISOMAP tends to overcluster the data. To alleviate this problem, this paper presented a new variant of ISOMAP called Weighted ISOMAP (WISOMAP), which used Weighted Multidimensional Scaling (WMDS) instead of Classical Multidimensional Scaling (CMDS) to map the data into the low-dimensional embedding space. As a new variant of MDS, WMDS gave smaller weight to the distances with more edges, which were generally worse approximated and then less trustworthy than those with fewer edges, and thus could limit the effects of the generally worse-approximated distances with many edges and preserved the more trustworthy distances with few edges in the low-dimensional embedding space more precisely, by which the data relying on an imperfect manifold could be visualized better. The efficiency of WISOMAP is verified by experimental results well.

Algorithm for minimizing determination finite automation based on information system

YANG Chuan-jian GE Hao YAO Guang-shun WANG Bo

2012, 32(07):  1991-1993.  DOI: 10.3724/SP.J.1087.2012.01991

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At present, Determination Finite Automation (DFA) minimization more focuses on theoretical research, and there are not many algorithms easy to achieve. Therefore, the method of minimization of determination finite automation was researched. First, DFA was converted into information system; and then the information system was simplified, which was based on the partition of equivalence classes; at last the simplified information system was converted into minimized DFA. Concerning the above process, an algorithm of minimizing DFA based on strategy of divide and conquer was proposed. In the average case, the time complexity and space complexity of the algorithm are O(n log n) and O(n) respectively. Finally, an example was used to explain the feasibility of the proposed algorithm.

Approximate subgraph matching based on dual index

HUANG Yun HONG Jia-ming QIN Zun-yue

2012, 32(07):  1994-1997.  DOI: 10.3724/SP.J.1087.2012.01994

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The fast increasing large and complex networks make the research of graph structure more and more important, in which approximate subgraph query is of big concern. Constructing index for each vertex by the adjacency characteristics was able to reduce the number of matched vertices, and partitioning the large graph based on label and structure information was able to reduce the matching search space. Using the dual index built in offline time, large amount of candidate vertices were filtered out according to the adjacency discriminant formula, and then the edge matching was carried out in some partition spaces. The experiments on real dataset show that, compared with many other existing methods, the dual-index query mechanism improves the efficiency and accuracy of subgraph matching significantly.

Information security

Backup and recovery mechanism of Web anti-tamper system based on LZMA and multi-version

ZHAO Bang HE Qian WANG Yong YAO Lin-lin

2012, 32(07):  1998-2002.  DOI: 10.3724/SP.J.1087.2012.01998

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Because the functions of backup and recovery are usually ignored in the web anti-tamper system, a web anti-tamper system model is proposed in this paper, based on which a safe and efficient remote backup and recovery system is given. The multi-version management technical of backup data is used for restoring the data of different versions and different periods. The Lempel-Ziv-Markov chain Algorithm(LZMA) is used to compress the backup data for improving the disk utilization. The Data Encryption Standard(DES) and File Transfer Protocol(FTP) are used for securable remote date storage and transmission. Finally, the system performance test shows it can effectively backup and recover the WEB Server data without affecting the WEB Server load and recover a single page within 100ms. It’s an effective means to solve the web tampering problem.

Adaptive anomaly detection method of Web-based attacks

WEN Kai GUO Fan YU Min

2012, 32(07):  2003-2006.  DOI: 10.3724/SP.J.1087.2012.02003

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Concerning the problem that untrusted sample can be easily introduced in traditional methods, an adaptive model was proposed in this paper. Based on the description of the structural feature of Request-URL, a whole sample set was divided into smaller subsets. The discreteness of a subset was calculated by its properties, which would determine whether the subset is normal. On basis of these, the detection model was created by the improved algorithm with the normal subsets, and dynamic update of model was achieved by Hidden Markov Model (HMM) merging. The experimental results show that the adaptive model built by the proposed method can effectively identify Web-based attacks and reduce false alert ratio.

Cryptanalysis of two smartcard-based remote user password authentication protocols

XUE Feng WANG Ding WANG Li-ping MA Chun-guang

2012, 32(07):  2007-2009.  DOI: 10.3724/SP.J.1087.2012.02007

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Since identity authentication becomes an essential mechanism to ensure robust system security in distributed networks, smartcard-based remote user password authentication protocols have been studied intensively recently. Two recently proposed smartcard-based authentication protocols were examined with the scenario-based attack techniques. The protocol presented in “Cryptanalysis and improvement of Liao et al. 's remote user authentication scheme” (PAN Chun-lan, ZHOU An-min, XIAO Feng-xia, et al. Improved remote user authentication scheme. Computer Engineering and Applications, 2010,46(4):110-112) can not withstand the offline password guessing attack as the authors claimed, while the protocol presented in “Improved scheme for smart card password authentication based on bilinear pairings” (DENG Li, WANG Xiao-feng. Improved scheme for smart card password authentication based on bilinear pairings. Computer Engineering, 2010,36(18):150-152) is found vulnerable to the Denial of Service (DoS) attack and insider attack. The analytical results show that, both protocols are susceptible to serious security threats and impractical for security-concerned applications.

Lightweight security authentication protocol for radio frequency identification

ZHANG Shun CHEN Hai-jin

2012, 32(07):  2010-2014.  DOI: 10.3724/SP.J.1087.2012.02010

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With regard to the security vulnerabilities of the existing Radio Frequency Identification (RFID) authentication protocols, a new lightweight security protocol for RFID was proposed. The formal proof of the correctness of the proposed authentication protocol was given based on GNY logic. The proposed scheme adopted the method of reader dual-authentication and key refreshing during reader pre-authentication phase, which achieved the anti-desynchronization requirement by adding flag Tm of malicious attacks into the tag. The protocol solved the security and privacy problems of poor scalability, location tracking due to failure of renewing the key of tag, and Denial of Service (DoS) resulting from illegal updating inner keys of tag/server in the existed schemes. It efficiently resisted several possible attacks including replay, tag/reader impersonation, traffic analysis, location tracking and desynchronization. The analytical results show that the proposed protocol is of low-cost, good security and limited computational complexity, which fits for RFID system when the tags number is large.

Efficient identity-based ring signature in standard model

YU Ting ZHAO Ze-mao REN Xi-feng

2012, 32(07):  2015-2017.  DOI: 10.3724/SP.J.1087.2012.02015

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The ring signatures in the standard model have too many pairings and multiple-known-signature encounters forgery attack, so a new efficient and safe ring signature was proposed. On the basis of reducing public parameters, a Hash function with secret was introduced into every member, so it achieved the best safety requirements and had the unconditional anonymity. Compared with the existing identity-based ring signature schemes in the standard model, for n members of a ring, the signature only needs two pairings to verify without pre-operation, thus it can greatly improve the efficiency.

Image encryption based on low density parity check coding and chaotic system

ZHAO Wen-bo TIAN Xiao-ping WU Cheng-mao

2012, 32(07):  2018-2021.  DOI: 10.3724/SP.J.1087.2012.02018

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To improve the security and reliability of image transmission, an image encryption algorithm based on combination Low Density Parity Check (LDPC) coding with chaotic system was proposed. Firstly, the algorithm used parity encoding to extend pixels' value of image into 10 bits and calculated its deviation acted as chaotic initial value. Secondly, Arnold transformation was used to scramble the positions of image pixels and Henon mapping was used to diffuse the values of pixels. Finally, the high 2 bits were separated from 10 bits of pixel value and transmitted faultlessly by LDPC code, the other 8 bits acted as the encryption result. The experimental results show that the proposed algorithm has strong sensitivity to the keys and plaintext, possesses favorable avalanche effect, and it can resist plaintext attack and differential attack effectively. Moreover, the encryption result has strong ability of resisting cutting and noise attacks.

Typical applications

Research on temporal and spatial distribution of online users in P2P TV

JIANG Zhi-Hong WANG Hui HUANG Bing LI Pei FAN Peng-yi

2012, 32(07):  2022-2026.  DOI: 10.3724/SP.J.1087.2012.02022

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Direct towards anonymity and high dynamic of online user in P2P TV, a P2P TV crawler, called TVCrawler was developed and deployed which enabled to launch an active measurement on several popular large scale P2P TV systems. The authors conducted a comparative research on time evolution and geographic distribution of online users in these different P2P TV systems. First, while intuitively researching the time evolution of online users in P2P TV channel, the method of MultiScale Entropy (MSE) analysis was introduced to investigate the complexity in time series of the number of online users. Second, the authors made a study on the regular pattern of online users' geographic distribution, and made a Google map-based visual representation about online users. Then, by analyzing the relationship between geographic distribution of online Chinese users and provincial economic development level of China, it is discovered that significant linear decreasing correlation exists between the two of them.

Survey on microblog research based on information data analysis

WANG jing ZHU Ke WANG Bin-qiang

2012, 32(07):  2027-2029.  DOI: 10.3724/SP.J.1087.2012.02027

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In recent years, with the advances in information communication and organizational ability, microblog has attracted the attention of scholars of all kinds. This paper reviewed the present study of microblog based on the information data analysis, and presented the concept of three components in microblog information transmission. Besides it summarized the main problems and methods in this field, generalized the domestic and foreign achievement. Finally, the trend for future work on the monitoring and management of microblog was discussed.

Green network automatic abstraction algorithm

LONG Long DENG Wei

2012, 32(07):  2030-2032.  DOI: 10.3724/SP.J.1087.2012.02030

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With the rapid development of Internet, the traditional automatic abstraction algorithm cannot meet the needs of the green network. Different from the traditional automatic abstraction algorithm based on statistical learning, this paper proposed a new algorithm based on clear semantics. It made use of cloud data acquisition library of green network system based on behavior analysis and Wikipedia resources as the knowledge base to establish the concept of space, it performed semantic interpretation on these words. Finally, the experimental results prove that the proposed method can cover more information with fewer sentences compared with the traditional algorithm, thus it greatly shortens the time for the system to analyze and filter inappropriate content and enhances the quality of software services.

Construction of Chinese polarity lexicon by integration of morpheme features

CHANG Xiao-long ZHANG Hui

2012, 32(07):  2033-2037.  DOI: 10.3724/SP.J.1087.2012.02033

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Concerning the dependence on seed words amount of the traditional method based on morpheme, and the low recall rate of traditional graph-based method, the authors proposed a method which integrated the morpheme relationship of Chinese words into the graph model, and combined the synonymy of words to build Chinese polarity lexicon by a semi-supervised learning algorithm in a graph. Firstly, a morpheme model was used to weight the similarity of two Chinese words. Secondly, synonymous words and bilingual lexicon were used to build the synonymy of words. Finally, the final relation was acquired by integrating the two relations, and Label Propagation (LP) was used to run on the relation map to distinguish the polarity of the emotion words. The experimental results show that the proposed method can achieve high accuracy and recall rate, and MicroF1 can be as high as 92.8%. The dependence on seed words amount is reduced based on the fact that when the seed word amount is 100, MicroF1 can still be 84.1%. In addition, the proposed method has fast convergence.

Text sentiment analysis-oriented commodity review detection

PANG Hai-jie

2012, 32(07):  2038-2040.  DOI: 10.3724/SP.J.1087.2012.02038

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To help sellers timely and effectively get the commodity reviews, the author proposed a commodity review detection method based on the key word extraction. Based on the Chinese word segmentation, this method firstly extracted the candidate keywords based on part of speech tagging, and then filtered out noises based on the rules. The paper extracted the dynamic co-occurrence of the commodity reviews, and extended the keywords based on these dynamic co-occurrences. Finally the commodity review detection method based on the keyword was realized. The experimental results show that, compared to the basic model, the proposed method can increase the F-Measure by 34.8%, which proves that efficient key word extraction is very useful to the commodity review detection.

Dependence relationships-based change probability metric: an experimental analysis

XUE Chao-dong YANG Yi-biao ZHOU Yu-ming

2012, 32(07):  2041-2043.  DOI: 10.3724/SP.J.1087.2012.02041

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It is essential for software development and maintenance to predict which modules are change-prone in an Object-Oriented (OO) software system. In this paper, a light-weight approach was developed to compute the change probability metric by leveraging the dependence relationships between classes in a system. Then, based on Logistic regression model, an experimental analysis was conducted using Eclipse 2.0. The experimental results indicate that, on one hand, the proposed change probability metric captures different information from traditional OO metrics. On the other hand, when being used with traditional OO metrics together, the proposed change probability metric can significantly improve the accuracy for predicting the change-prone classes.

Research into community structure of resting-state brain functional network

WANG Yan-qun LI Hai-fang GUO Hao CHEN Jun-jie

2012, 32(07):  2044-2048.  DOI: 10.3724/SP.J.1087.2012.02044

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The community detecting algorithm was applied to human functional network to explore the mechanism of human brain. The brain functional data of 28 healthy subjects were collected by functional Magnetic Resonance Imaging (fMRI), and the brain functional network of human beings based on time series was constructed. A threshold range of vertices in the network was designated according to modularity and full connected network theory. The community structures were detected by using the hierarchical clustering algorithm and the greedy algorithm respectively, and the experimental results show that similar community structures have been obtained. Then different performances can be explored across the threshold by analyzing the modularity. An effective threshold range of vertices between 180 to 320 in brain network was proposed. Exploring the community structure is helpful to comprehend the mechanism of brain lesions, which provides a tool for diagnosis and treatment of brain diseases.

Large scale database face recognition based on region constriction

LI Chao-you SUN Ji-zhou

2012, 32(07):  2049-2052.  DOI: 10.3724/SP.J.1087.2012.02049

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To increase face recognition speed and reduce RAM occupancy on a large-scale database, a high-efficient face recognition method was proposed. By introducing the technique of Discrete Cosine Transform (DC) image data compression into the face feature database compression, the database was compressed in multi-level compression ratio to generate few compressed sub-databases. Then, according to the order from high-to-low compression ratio, the rough face recognition was implemented on these sub-databases one by one. In the meantime, the recognition scope was narrowed down progressively according to previous recognition results. Finally, the accurate face recognition was carried out on the original uncompressed database in a very small range. Compared to traditional method, the experimental results show that the recognition time is reduced to 29.2%, RAM occupancy is reduced to 10.2%, and hard disk resource consumption is increased by only 11%, and the recognition rate is not significantly reduced.

Fuzzy clustering of complex equipment maintenance for equipment health management

DU Jun-le XIA Liang-hua QI Wei-wei DOU Jian-bin

2012, 32(07):  2053-2055.  DOI: 10.3724/SP.J.1087.2012.02053

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Scientific and reasonable maintenance activity is an important way to improve equipment efficiency and combating force of troops. Complex equipment demands higher reliability, maintainability and supportability, which brings new problems to maintenance activity. When to maintain and how to maintain play an important role in exerting the equipment's efficiency. This paper put forward a strategy model for maintenance activity from Equipment Health Management (EHM) point of view. Based on the analysis of health status, failure mode effect and failure mode probability, Fuzzy C-Means (FCM) clustering algorithm was used to research maintenance activity. Maintenance opportunity was differentiated and a proper maintenance strategy was proposed. Thus appropriate maintenance was made at appropriate opportunity. This could optimize maintenance activity as well as realize EHM goal. The simulation results with Matlab show that the proposed method is feasible and reasonable, which can support EHM decision making.

Design and implementation of remote data backup and recovery system based on Linux

SU Guan-qun TAO Hong-cai

2012, 32(07):  2056-2058.  DOI: 10.3724/SP.J.1087.2012.02056

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In this paper, a Remote Data Backup and Recovery System (RDBRS) was presented and implemented to improve the efficiency of data disaster recovery. Through improving the frame of Rsync, the system used Inotify and snapshot to locate files that have been changed and to get file increments, and used Rsync to transfer data remotely. In this way, the system resource consumption and the amount of network traffic were greatly reduced, and data transmission speed increased about 10MBps compared to Rsync in gigabit network environment. The experimental results show that the system has high practical value to small and medium enterprises without enough fund.

Model design of entity and damage effect of precision guided ammunition

YUAN Hui WANG Feng-shan

2012, 32(07):  2059-2062.  DOI: 10.3724/SP.J.1087.2012.02059

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To solve the semantic heterogeneity and sharing problems in the simulation process of precision guided ammunition operations, the entity and domino effect model was erected on the basis of ontology engineering. With the system model description of the precision guided ammunition and its damage effect, the description semantics was advanced by the precision guided ammunition ontology. Then the solution for design and construction of ontology was given, and the ontology system for precision guided ammunition domain was determined. Based on the ample share foundation of precision guided ammunitions, the simulation precision guided ammunition model was practically designed and applied to the damage simulation experiment from the guided ammunition to protective structure, which established the foundation for the knowledge management of the entity and damage effect with ontology engineering.

Feature extraction in time-frequency analysis of radar signal sorting

CHEN Diao ZHANG Deng-fu YONG Xiao-ju HU Xu-ming

2012, 32(07):  2063-2065.  DOI: 10.3724/SP.J.1087.2012.02063

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According to the high complexity of extracting feature of radar signal using image processing method, a new method for extracting feature was proposed. Firstly, the time-frequency distribution was gained based on the adaptive Gaussian kernel time frequency analysis, then through analyzing the physical meaning of each element, one dimension vector could be found through a simple arithmetic instead of the complicated method through processing the time-frequency figure with image processing means, so the real-time requirement for sorting radar signal could be satisfied. The simulation results verify the efficiency of the proposed algorithm. Additionally, the accuracy can be kept at a high level while the Signal-to-Noise Ratio (SNR) is low.

Multi-target track-before-detect algorithm based on joint multi-target probability density model

FAN Ling ZHANG Xiao-ling

2012, 32(07):  2066-2069.  DOI: 10.3724/SP.J.1087.2012.02066

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Concerning the problem of Track-Before-Detect (TBD) in a multi-target environment, in this paper, a TBD algorithm based on Joint Multi-target Probability Density (JMPD) model was proposed. The JMPD was a single probabilistic entity that captured uncertainty about the number of targets present in the surveillance region as well as their individual states and a Particle Filter (PF) was used to recursively estimate the JMPD. The simulation results demonstrate that the birth and death of target can be estimated accurately as well as its trajectory by the proposed algorithm with smaller detection delays.

Robust speech recognition by adopting random projection in feature space

ZHOU A-zhuan YU Yi-biao

2012, 32(07):  2070-2073.  DOI: 10.3724/SP.J.1087.2012.02070

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To improve speech recognition in noisy environment such as in driving car, a new method which adopted Random Projection (RP) of feature space was proposed in this paper. First, original speech feature coefficients were projected into a new feature space using random matrixes to make the new coefficients have distribution more similar to the Gaussian but preserve the original distances among features with maximum probability. Then Hidden Markov Model (HMM) of every word was trained. In the test stage, the initial pattern matching results were further processed with majority voting strategy then to make a final speech recognition decision. The experimental results based on speech recognition database CENSREC-2 of Japan Information Processing Association demonstrate the effectiveness of random projection of feature space, which greatly improves the speech recognition performance in driving car.

Improved transfer logic of two-path algorithm for acoustic echo cancellation

WANG fei LIU Chang

2012, 32(07):  2074-2077.  DOI: 10.3724/SP.J.1087.2012.02074

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The two-path algorithm in the acoustic echo cancellation is widely applied to avoid the false adaptation problem during the double-talk situation. This paper proposed an improved transfer logic for the two-path algorithm; based on the comparison of the Echo Return Loss Enhancement (ERLE) for the filters, the improved transfer logic decided whether to permit filter update. Furthermore, the improved transfer logic managed to detect the double-talk and avoid the false filter update, improved the convergence speed and allowed the reduction of the memory requirement and computational complexity. The simulation results show the improved performance of the proposed solution.

Improved least mean square adaptive filter algorithm

WANG Cheng-xi LIU Yi-an ZHANG Qiang

2012, 32(07):  2078-2081.  DOI: 10.3724/SP.J.1087.2012.02078

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Concerning the contradiction between convergence speed and convergence precision when the traditional fixed pace Least Mean Square (LMS) algorithm was used to radar clutter adaptive filter system, the paper put forward a new kind of variable-pace adaptive filter algorithm. Through combining the relevant error and the former pace to real-time update next iteration of the pace in its basic pace iterative formula, which could reach with higher convergence speed and smaller disorder, and it also could prevent the bad effect from the existing related noise. The simulation results show that, compared with the traditional fixed-pace LMS algorithm and context improved algorithm, the convergence rate, convergence accuracy and noise prevention have been greatly improved. It proves that the proposed algorithm is effective, feasible, and consistent with the theoretical analysis.

Design of remote heart rate monitoring system based on GSM

ZHENG Zheng-bing ZHAO Feng

2012, 32(07):  2082-2084.  DOI: 10.3724/SP.J.1087.2012.02082

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According to the electrocardiograph signal characteristics of human body, a wireless heart rate monitoring system based on Global System for Mobile communications (GSM) was proposed. It was composed of the acquisition terminal and the monitoring terminal. The optical pulse sensor HKG-07B of the acquisition terminal acquired pulse signal on the human body which was adjusted as the output signal and then the SPCE061A completed the data computation, storage, display and voice broadcast. On the basis of the calculated value of the heart rate, the TC35I module used the mean of short message to achieve the remote alarm received by the monitoring terminal. The experimental results show that: the accuracy of the acquired heart rate data meets the performance requirements, and real-time wireless heart rate monitoring can be achieved.