Table of Content

01 April 2014, Volume 34 Issue 4

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Network and communications

Location-free and energy-balanced topology control for wireless sensor networks

CHENG Chen BAI Guangwei ZHAO Lu SHEN Hang

2014, 34(4):  921-925.  DOI: 10.11772/j.issn.1001-9081.2014.04.0921

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This study begins with a Location-free Topology Construction (LTC) algorithm to construct a virtual backbone based on connected dominating tree, in consideration of the characteristics of densely deployed Wireless Sensor Network (WSN). On this basis, the energy consumption of backbone nodes and the data transmission delay were analyzed. Then, a density control factor and a rate control factor for data transmission were introduced to balance energy consumption of the virtual backbone construction, and a Location-free and Energy-balanced Topology Control (LETC) algorithm, as an extension of LTC, was proposed. In accordance with the amount of data transmission in difference regions, LETC adjusted arrangement density of virtual backbone nodes, and increased the node transmission rate of nodes to reduce network latency. Both theoretical analysis and simulation results demonstrate that LETC algorithm can effectively balance energy consumption, extending the network lifetime by 24.1%, and reducing the transimisson delay by 28.1% compared to LTC. 〖BP(〗In the case of data transmission delay, the reduction achieved is up to 28.1%.〖BP)〗

Routing hole optimization algorithm based on direction-angle in WMSN

SUN Yi HUANG Kexin WU Xin LU Jun

2014, 34(4):  926-929.  DOI: 10.11772/j.issn.1001-9081.2014.04.0926

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As a kind of pure location routing algorithm in Wireless Multimedia Sensor Network (WMSN), Two Phase Geographic Greedy Forwarding (TPGF) helps to select the next-hop node which is of nearest distance to the destination from neighbor ones. In some cases, the distance between the next-hop node and the destination node could be farther than that of the current node and the destination node; At the same time, by numbering the nodes, TPGF solves the problem of hole and satisfies the Quality of Service (QoS) requirements. In line with the strategy of selecting the next-hop node farther than the current node, action-angle variables and DATF (Direction-Angle Greedy Forwarding) algorithm were introduced to guarantee and optimize the process of selecting the bound nodes. The simulation result indicates that DATF algorithm shows better performance than TPGF in both energy consumption and end-to-end transmission delay and also has a significant effect on solving the problem of hole.

Virtual network embedding algorithm based on a hybrid swarm intelligence optimization

WANG Wengao WANG Binqiang WANG Zhiming XING Chiqiang

2014, 34(4):  930-934.  DOI: 10.11772/j.issn.1001-9081.2014.04.0930

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Network virtualization is recognized as a significant technology to solve the ossification of current Internet. Virtual Network Embedding (VNE) is a major challenge in network virtualization. The main object of VNE is to increase the acceptance ratio of Virtual Network (VN) and the revenue of infrastructure providers. Regarding VNE as an Integer Linear Programming (ILP) model with an assumption that substrate network needs to support path splitting, a new VNE algorithm based on hybrid swarm intelligence optimization was proposed. The proposed algorithm took advantage of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to optimize the mapping scheme in view of the balance of the mapping overhead and the mapping proportionality. Compared with the existing mainstream approaches, the simulation results demonstrate that the proposed algorithm can increase the long-term average revenue and acceptance ratio.

Research on cascading invulnerability of community structure networks under intentional-attack

LI Minhao DU Jun PENG Xingzhao DING Chao

2014, 34(4):  935-938.  DOI: 10.11772/j.issn.1001-9081.2014.04.0935

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In order to investigate the effects of community structure on cascading invulnerability, in the frame of a community structure network, the initial load of the node was defined by its betweenness, and the load on the broken node was redistributed to its neighboring nodes according to the preferential probability. When the node with the largest load being intentionally attacked in the network, the relation of load exponent, coupling-strength in a community, coupling-strength between communities, modularity function and the network's invulnerability were studied. The results show that the network's cascading invulnerability is positively related with coupling-strength in a community, coupling-strength between communities and modularity function, negatively related with load exponent. With comparison to BA (Barabási-Albert) scale-free network and WS (Watts-Strogatz) small-world networks, the result indicates that community structure lowers the network's cascading invulnerability, thus the more homogeneous betweenness distribution is, the stronger network's cascading invulnerability is.

Asymmetric Information Power Game Mechanism Based on Hidden Markov

ZHU Jiang ZHANG Yuping PENG Zhenzhen

2014, 34(4):  939-944.  DOI: 10.11772/j.issn.1001-9081.2014.04.0939

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To solve the issue that, in wireless resource competition, the environment information which gamers get in power game is asymmetric, a power game mechanism based on hidden Markov prediction was proposed. By establishing a Hidden Markov Prediction Model (HMPM), the proposed mechanism estimated whether competitors would take part in the game to improve the information accuracy of the game. Then, the predicted information was used to calculate the best transmission power via the cost function. The simulation results show that, compared with MAP (Maximum A Posteriori) method and NP (No Predicting) method, the power game model based on hidden Markov prediction can not only meet the target capacity, but also improve the power efficiency of the unauthorized users.

Performance evaluation of IEEE 802.11p MAC protocol based on NCTUns

CHEN Siyang ZHU Xiping WEN Hong

2014, 34(4):  945-949.  DOI: 10.11772/j.issn.1001-9081.2014.04.0945

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The IEEE 802.11p standard plays an important role in the application and deployment of Vehicular Ad-hoc Network (VANET). Aiming at improving former literature' shortage including the incomplete use of simulation scenes and WAVE (Wireless Access in Vehicular Environments) communication mode, simulation based on NCTUns (National Chiao Tung University network simulation) was conducted to study the effect of transmission power, transmission distance, vehicle density and vehicle velocity on network performance after illustrating the architectures of IEEE 802.11p, NCTUns and the simulation process. The simulation results indicate that node density, transmission power and transmission distance can remarkably influence the packets reception rate and throughput while vehicle velocity has no effect on the node throughput. Finally a method of joint adjustment of packets reception rate and contention window was proposed to enhance the MAC (Media Access Control) performance of the VANET.

Method of IPv6 neighbor cache protection based on improved reversed detection

KONG Yazhou WANG Zhenxing WANG Yu ZHANG Liancheng

2014, 34(4):  950-954.  DOI: 10.11772/j.issn.1001-9081.2014.04.0950

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IPv6 Neighbor Cache (NC) was very vulnerable to be attacked, therefore, an improved method named Reversed Detection Plus (RD+) was proposed. Timestamp and sequence were firstly introduced to limit strict time of response and response matching respectively; RD+ queue was defined to store timestamp and sequence, and Random Early Detection Based on Timestamp (RED-T) algorithm was designed to prevent Denial of Service (DoS) attacks. The experimental results show that RD+ can effectively protect IPv6 NC to resist spoofing and DoS attacks, and compared with Heuristic and Explicit (HE) and Secure Neighbor Discovery (SEND), RD+ has a low consumption of resources.

Passive queue management algorithm based on cloud model

CHEN ZhiJun

2014, 34(4):  955-957.  DOI: 10.11772/j.issn.1001-9081.2014.04.0955

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In order to mitigate the network performance reduction by congestion problem, a new Passive Queue Management (PQM) algorithm named Drop Front n based on Cloud Model (DFCM) was proposed with drop front. At first, the drop packet strategy and drop packet probability were presented by considering network queue length and arrival rate in this algorithm, and the actual queue length was computed with cloud model. Finally, a simulation with NS2 and Matlab was conducted to study the key influencing factors of this algorithm. The results show that, compared with Drop Tail and DFSQ (Drop Front n based on Synchronized Queue) algorithms, DFCM has better suitability in instantaneous queue length variance and effective packet transmission.

Satellite terminal bursty traffic model and queuing performance analysis

BIE Yuxia ZHAN Zhaxin LIU Haiyan

2014, 34(4):  958-962.  DOI: 10.11772/j.issn.1001-9081.2014.04.0958

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With the increase of application of satellite networks in emergency communication, and continuous growth of satellite terminal service types, the traffic may experience an instant augmentation showing a significant burst, and the data flow on the terminal also presents self-similarity. A method was propsed to generate satellite terminal self-similar traffic flow by using a superposition ON/OFF model with heavy-tailed distribution of time interval. And the effect of input of self-similar traffic flow on the packet loss rate, delay, and delay jitter was discussed, as well as the requirements on effective bandwidth. The relationship between packet loss rate at network terminal, delay, delay jitter and system cache was obtained by simulation, based on which, a method was put forward to reduce delay and decrease packet loss rate, providing theoretical support for efficient information transmission under condition of limited bandwidth and system cache.

Multi-user chaotic communication and its bit error rate based on orthogonal chaos

LI Dujuan ZHOU Zifeng WU Cheng-mao

2014, 34(4):  963-968.  DOI: 10.11772/j.issn.1001-9081.2014.04.0963

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In the multi-user chaotic communication system, the increase in the number of communication users as well as the quasi-orthogonality between chaotic sequences cause channel interference. Therefore, the Bit Error Rate (BER) of multi-user chaotic communication system, in which different chaotic signals used Schmidt orthogonalization method to produce the corresponding orthogonal chaotic sequences as spreading code, was studied in Additive White Gaussian Noise (AWGN) and Rayleigh fading channel. Firstly, the statistical autocorrelation and cross-correlation characteristics of each orthogonal chaotic sequence were taken as an important index to measure the performance of orthogonal chaotic spreading code sequence, and the statistical correlated characteristics of each orthogonal chaotic sequence and both the mean and variance of the cross-correlation curve were tested and analyzed. Secondly, the BER of each orthogonal chaotic spreading code was obtained by two channel simulation experiments, and the intrinsic correlation found by contrasting the BER of orthogonal chaotic spreading code and its corresponding statistical correlated characteristics was revealed at that time. Lastly, the BERs of multi-user chaotic communication system of two different channels were compared and analyzed and the effect on BER caused by different channels was revealed. The simulation results show that the space-time orthogonal chaotic sequence of phase space chaotic signals can obtain low BER in the two channels, and especially, space-time orthogonal chaotic sequence can obtain lower BER in Rayleigh fading channel, and also show that the proposed method can effectively reduce the interference between the channels in the multi-user communication and is more conducive to the needs of multi-user communication.

Improved algorithm for vital arc of maximum dynamic flow

LIU Yangyang XIE Zheng CHEN Zhi

2014, 34(4):  969-972.  DOI: 10.11772/j.issn.1001-9081.2014.04.0969

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For the vital arc problem of maximum dynamic flow in time-capacitated network, the classic Ford-Fulkerson maximum dynamic flow algorithm was analyzed and simplified. Thus an improved algorithm based on minimum cost augmenting path to find the vital arc of the maximum dynamic flow was proposed. The shared minimum augmenting paths were retained when computing maximum dynamic flow in new network and the unnecessary computation was removed in the algorithm. Finally, the improved algorithm was compared with the original algorithm and natural algorithm. The numerical analysis shows that the improved algorithm is more efficient than the natural algorithm

Proportional delay guarantee on Web server based on decentralized self-tuning control

GUO Guang ZHANG Yanxin

2014, 34(4):  973-976.  DOI: 10.11772/j.issn.1001-9081.2014.04.0973

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Single-variable model is generally used for Apache Web server. It has poor scalability when it is used to handle multiple priorities delay guarantee. A Multi-Input Multi-Output (MIMO) system model for Web server was proposed with decentralized self-tuning controllers based on decentralized control theory and Self-Tuning Control (STC) theory. These controllers could dynamically adjust the number of worker threads, which handled different priority requests to ensure that the higher priority requests were processed faster and the average delay ratio of different priority was maintained the same as settings. The parameters of model and controllers were updated according to the result of online identification. The results of simulation tests indicate that proportional delay guarantee can be maintained on the Web server in the closed-loop system even if the number of concurrent client connections change abruptly under overload conditions.

Noise reduction of chaotic signals based on high-order threshold function and wavelet packet

YANG Shan WANG Jian

2014, 34(4):  977-979.  DOI: 10.11772/j.issn.1001-9081.2014.04.0977

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The conventional threshold function in wavelet noise reduction of chaotic signals has its shortages, such as low resolution of high frequency and restraint limit of quantitative method to hard and soft thresholds. Concerning these shortages, a wavelet packet noise reduction method of chaotic signals was proposed based on a high-order threshold function. The method could further decompose high frequency part by wavelet packet and retained useful high-frequency information, so it was more precious in partial analysis. Furthermore the threshold function was continuous and derivable. There was a smooth transiting area between noise wavelet coefficient and chaotic signal wavelet coefficient. As a result, it is more consistent with the continuous characteristics of the signal. The comparative simulation shows that, compared with soft threshold noise reduction method and semi-soft threshold wavelet packet noise reduction method, the effect of noise reduction to chaotic signals has been significantly improved, and Signal-to-Noise Ratio (SNR) increased 3.7-7dB.

Survey of influence in social networks

XIA tao CHEN Yunfang ZHANG Wei LU Youwei

2014, 34(4):  980-985.  DOI: 10.11772/j.issn.1001-9081.2014.04.0980

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In the field of social influence propagation, social network as the media plays a fundamental role in interaction between social individuals and disseminating information or views. First, the definition of social influence and the essential attribute of social influences as the social relevance were discussed. Then, the independent cascade model and the linear threshold model were expounded, as well as greedy algorithm and heuristic algorithms which can confirm the influential people. Finally, the new trend of research on social influence, such as community-based influence maximization algorithm and research on the influence of multiple subjects and multiple behaviors were deeply analyzed.

Fountain code based data recovery system for cloud storage

PENG Zhen CHEN Lanxiang GUO Gongde

2014, 34(4):  986-993.  DOI: 10.11772/j.issn.1001-9081.2014.04.0986

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As a new service for data storage and management, cloud storage has the virtue of portability and simplicity in use. However, it also prompts a significant problem of ensuring the integrity and recovery of data. A data recovery system for cloud storage based on fountain code was designed to resolve the problem. In this system, the user encoded his data by fountain code to make the tampered data recoverable, and tested the data's integrity with Hash functions so that the complexity in data verification and recovery was reduced. Through this system, the user can verify whether his data have been tampered or not by sending a challenge to the servers. Furthermore, once some data have been found tampered, the user can require and supervise the servers to locate and repair them timely. The experimental results show that the data integrity detection precision reaches 99% when the data's manipulation rate is 1%-5%.

Trust model based on user types and privacy protection for personalized cloud services

LIU Fei LUO Yonglong GUO Liangmin MA Yuan

2014, 34(4):  994-998.  DOI: 10.11772/j.issn.1001-9081.2014.04.0994

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Concerning the problem that it is difficult for the users in cloud computing to obtain the high-quality and personalized cloud services provided by a large number of cloud providers, a trust model based on user types and privacy protection for the personalized cloud services was proposed. Firstly, the users were divided into familiar users, strange users and normal users according to the transaction history. Secondly, a fair and reasonable trust evaluation Agent was introduced to protect users' privacy, which could evaluate the trust relationship between requesters and providers based on the user types. Lastly, in view of the dynamics of trust, a new updating mechanism combined with the transaction time and transaction amount was provided based on Quality of Service (QoS). The simulation results show that the proposed model has higher transaction success rate than AARep and PeerTrust. The transaction success rate can be increased by 10% and 16% in the harsh environment where the malicious user ratio reaches 70%. This method can improve transaction success rate, and has a strong ability to withstand harsh environments.

Dynamic resource management mechanism of debris resources in cloud computing

WANG Xiaoyu CHENG Lianglun

2014, 34(4):  999-1004.  DOI: 10.11772/j.issn.1001-9081.2014.04.0999

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Concerning the problems that resources specifications and services required by users were not entirely consistent and the full resources were cut into debrises in the process of resource reservation in cloud computing environment, a dynamic resources management strategy considering the reuse of debris resources was put forward. The causes of debris resources were studied to construct debris resource pools, and the metric was made to measure how many tasks the debris resource could receive. While taking full account of the current task for resource discovery, scheduling, matching, the resource partitioning was further discussed by task scheduling, and the influence of the receiving capacity of subsequent tasks of resources debris was indicated. Finally, a dynamic resource debris scheduling model was built. The theoretical analysis and Cloudsim simulation results prove that, the resource management strategy can achieve resource optimization and reorganization of resources debris effectively. The strategy can not only improve the resources reception capability for subsequent tasks but ensure high resource utilization.

Design and implementation of loop instruction buffer in VLIW processor

LI Yong HU Huili YANG Huanrong

2014, 34(4):  1005-1009.  DOI: 10.11772/j.issn.1001-9081.2014.04.1005

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Loop program has a significant amount of execution time in digital signal processing software, temporary storage of loop code with instruction buffer can reduce the number of program memory access to improve the performance of processor. A loop instruction buffer was added in the instruction pipeline. It could store and dispatch instructions of loop program in the software pipelining manner. The instructions of loop program needed to be accessed from program memory only once but executed many times, so the number of memory access was reduced. During the loop instructions were dispatched from buffer, the program memory could be signaled to sleep to reduce the power consumption of processor. In the typical application program, the instruction pipeline can be idle above 90%, and the performance of processor is improved about 10%, the overhead of loop buffer is 9% of the instruction pipeline.

MapReduce tasks scheduling model based on matching rules

JIN Weijian WANG Chunzhi

2014, 34(4):  1010-1013.  DOI: 10.11772/j.issn.1001-9081.2014.04.1010

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MapReduce is one of the popular distributed computing frameworks based on an open source cloud platform named Hadoop. However, the First-In First-Out (FIFO) scheduling algorithm of MapReduce is inefficient in resources utilization. A new tasks scheduling model based on resources matching rules was proposed and implemented. After obtaining the tasks resources requirement and remainder resources on computing nodes, the model assigned tasks to computing nodes based on resources matching degree to improve the usage efficiency of system resources. First of all, the model for MapReduce scheduling was established, the quantitative definition of resources and matching degree were given, and the corresponding calculation formulas were put forward. Second, the specific methods of resource measurement and the implementation of the algorithm were introduced. Compared with FIFO scheduling algorithm on TeraSort, GrepCount and WordCount, the experimental results show that the proposed model reduces by 22.19% in tasks completion time in the best case, and increases by 25.39% in throughput even in the worst case.

Communication code generation for automatic parallelization of irregular loops

FU LiGuo YAO Yuan DING Rui

2014, 34(4):  1014-1018.  DOI: 10.11772/j.issn.1001-9081.2014.04.1014

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Irregular computing exists in large scale parallel application widely and the automatic parallelization on distributed memory is hardly to generate parallel code for irregular loops at compile-time. The communication code of the parallel code influences the correctness and the efficiency to the runout of the program. It could automatically generate useful communication code for a common class of irregular loops at compile-time by using the approach of partial communication redundancy, that needed analyzing the array redistribution graph of the program to maintain the producer-consumer relation of irregular array references. The approach searched the local definition set of the irregular array on each processor by computation decomposition and accessed expression of array references as the communication data set, then analyzed the communication strategies for such irregular loops and generated the corresponding communication code. The experimental results show the validity of the approach and the expectant speedup of test applications.

Security Analysis of Range Query with Single Assertion on Encrypted Data

GU Chunsheng JING Zhengjun LI Hongwei YU Zhimin

2014, 34(4):  1019-1024.  DOI: 10.11772/j.issn.1001-9081.2014.04.1019

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To protect users' privacy, users often transfer encrypted sensitive data to a semi-trustworthy service provider. Cai et al.(CAI K, ZHANG M, FENG D. Secure range query with single assertion on encrypted data ［J］. Chinese Journal of Computers, 2011, 34(11): 2093-2103) first presented the ciphertext-only secure range query scheme with single assertion on encrypted data to prevent information leakage of users' privacy, whereas the previous schemes of range query on encrypted data were implemented through many assertions. Applying principle of trigonometric functions and matrix theory, the rank of the sensitive data was directly generated from protected interval index. Hence, this scheme was not ciphertext-only secure. To avoid this security drawback, a secure improvement scheme was constructed by introducing random element, and its complexity was analyzed.

Technique of cryptographic function filtration based on dynamic loop information entropy

LI Jizhong JIANG Liehui SHU Hui CHANG Rui

2014, 34(4):  1025-1028.  DOI: 10.11772/j.issn.1001-9081.2014.04.1025

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For malware analysis and cipher application security validating, identification and filtration of cryptographic function from binary code has great significance. The memory operation and basic block loop characters were analyzed from cryptographic functions. According to the theory of binary data's information entropy, the characteristic of high-entropy of cryptographic algorithms was verified, a cryptographic functions filtration model was constructed based on dynamic loop entropy, and the hybrid (dynamic and static) method was adopted to reconstruct dynamic memory data in basic block loop. The experimental result shows that the filtration model has reliability and veracity.

Privacy preserving clustering algorithm based on wavelet transform for distributed data

XUE Anrong LIU Bin WEN Dandan

2014, 34(4):  1029-1033.  DOI: 10.11772/j.issn.1001-9081.2014.04.1029

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The existing privacy preserving clustering data mining algorithms cannot meet better trade-off between efficiency and privacy. To resolve this problem, a distributed privacy preserving clustering algorithm based on Secure Multi-party Computation (SMC) combined with perturbation was proposed. Data owners utilized the wavelet to achieve both data reduction and information hiding, and rearranged the attribute columns randomly to prevent data reconstruction which has potential danger of causing information disclosure. The proposed algorithm reduced computation and communication cost because it only used reduced data in its computation. Thus the efficiency of the algorithm was improved. At the same time, the incorporation of multiple protection measures in the computation effectively preserved data privacy. The clustering accuracy was less affected because of the high dependability of wavelet transform. The theoretical analysis and experimental results indicate that the proposed algorithm is secure and highly effective, and the overall F-measure and the efficiency of the proposed algorithm outperform the DCT-H (Discrete Cosine Transform-Haar) algorithm when dealing with high-dimensional datasets. Above all, it effectively resolves the trade-off issue between efficiency and privacy.

Design and implementation of virtual machine traffic detection system based on OpenFlow

SHAO Guolin CHEN Xingshu YIN Xueyuan ZHANG Fengwei

2014, 34(4):  1034-1037.  DOI: 10.11772/j.issn.1001-9081.2014.04.1034

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The virtual machines in cloud computing platform exchange data in the shared memory of physical machine. In view of the problem that the traffic cannot be captured and detected in firewall or other security components, the OpenFlow technology was analyzed, and a traffic redirection method based on OpenFlow was presented. To control traffic forwarding process and redirect it to security components, the method provided network connection for virtual machines with OpenFlow controller and virtual switches instead of physical switches, and built a traffic detection system composed of four modules including virtual switch, control unit, intrusion detection and system configuration management. The experimental results show that the proposed scheme can realize traffic redirection and the subsequent detection processing, and the system can provide switch-level and host-level control granularity. It also solves traffic detection problem under cloud computing environment in traditional scene by traffic redirection, and provides great expansion of the traffic processing based on OpenFlow.

Identity-based conditional proxy broadcast re-encryption

PAN Feng GE Yunlong ZHANG Qian SHEN Junwei

2014, 34(4):  1038-1041.  DOI: 10.11772/j.issn.1001-9081.2014.04.1038

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In traditional Proxy Re-Encryption (PRE), a proxy is too powerful as it has the ability to re-encrypt all delegator's ciphertexts to delegatee once the re-encryption key is obtained; And for more than one delegatees, delegator needs to generate different re-encryption key for different delegatee, which wastes a lot of resources in the calculation process. To solve these problems, an identity-based conditional proxy broadcast re-encryption was introduced. The delegator generated a re-encryption key for some specified condition during the encryption, like that the re-encryption authority of the proxy was restricted to that condition only. Moreover, the delegator's ciphertexts could be re-broadcasted to ensure the important communication and save a lot of computation and communication cost. Finally, the theoretical analysis verified the security of the scheme.

Security-analysis of a kind of generalized group-oriented threshold signcryption schemes

MO Lequn GUO Gengqi LI Feng

2014, 34(4):  1042-1046.  DOI: 10.11772/j.issn.1001-9081.2014.04.1042

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The threshold signcryption is a very useful cryptographic primitive. Recently, a generalized group-oriented threshold signcryption scheme was proposed by Peng et al.(PENG C, LI X, LUO W. A generalized group-oriented threshold signcryption schemes ［J］. Acta Electronica Sinica, 2007, 35(1): 64-67), but Wang (WANG Y. Cryptanalysis and improvement of threshold signcryption scheme ［J］. Computer Engineering and Applications, 2012, 48(1): 125-127) pointed out that there was a weakness in it because of the management of the keys, and an improved scheme was given. But both of the two schemes have the similar encryption structure, that is, if some members of the signcryption group colluded together in the key generation stage, they could avoid the authentication and deny that they had taken part in process of the signcryption. Furthermore, an improved group-oriented threshold signcryption scheme was proposed to resist the above attack and the attack proposed by Wang. It not only inherits the advantages of the above schemes, but also is more efficient in the process of parameters exchange.

Attribute-based encryption scheme combined with trust management in wireless sensor network

HUANG Dan

2014, 34(4):  1047-1050.  DOI: 10.11772/j.issn.1001-9081.2014.04.1047

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To solve the attributes authority and attributes revocation of Attribute-Based Encryption (ABE) in Wireless Sensor Network (WSN), a scheme of trust management-based ciphertext-policy ABE (TM-CP-ABE) was proposed. The proposed scheme was based on ciphertext-policy ABE and combined it with trust management mechanism. The procedure and the steps of trust evaluation based attributes authority and trust update based attributes revocation were provided. The security, complexity and validity of the proposed scheme were analyzed. Compared with the popular encryption scheme in WSN through comprehensive simulation, the results show that the proposed scheme is efficient for attribute revocation of CP-ABE in WSN. By attributes revocation, to a certain extent, the attacks of malicious nodes are also inhibited.

Access control model based on trust of users' behavior in cloud computing

ZHANG Kai PAN Xiaozhong

2014, 34(4):  1051-1054.  DOI: 10.11772/j.issn.1001-9081.2014.04.1051

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Considering the problem that the role of the user cannot be changed dynamically over time in access control model of cloud computing, a new access control model was proposed based on trust of users' behaviors for cloud computing. The trust level was determined according to the trust value synthesized from direct trust and recommendation trust, the roles were activated and granted permission to access resources, then services provided the requested resources, so as to achieve the purposes of access control. Besides, the basic elements and implementation process were proposed. The experimental results demonstrate that the proposed model can improve the objectivity of the trust evaluation of users' behaviors, and it can resist all illegal users access to cloud computing and enhance reliability and security of the data in cloud computing.

Artificial intelligence

Group mosquito host-seeking algorithm

LIU Xiaoting FENG Xiang YU Huiqun

2014, 34(4):  1055-1059.  DOI: 10.11772/j.issn.1001-9081.2014.04.1055

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Concerning the optimization of the overall complexity problem on the high-performance computing platform, a new algorithm named Group Mosquito Host-Seeking Algorithm (GMHSA) was proposed. GMHSA was an intelligent optimization algorithm inspired by mosquitoes sucking blood behavior. It involved max-min fairness and group interaction behavior. The producer group was chosen according to the concept of leader decision and the leadership functions were constructed to make each group maintain their own superiority as well as getting rid of local optimal solution. The algorithm was tested by Traveling Salesman Problem (TSP) and compared with other swarm intelligent algorithms. In the parallel experiment of 16 nodes, the speedup of GMHSA was 15.8, which was nearly linear speedup. Moreover, it could be directly used to solve transport problems and other practical optimal problems. The results indicate that GMHSA has highly parallelism and scalability, and it is an effective measurement for solving complex optimal problems involving behavior.

Shuffled fruit fly optimization algorithm with local deep search

LIU Chengzhong HUANG Gaobao ZHANG Renzhi CHAI Qiang

2014, 34(4):  1060-1064.  DOI: 10.11772/j.issn.1001-9081.2014.04.1060

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In order to overcome the demerits of poor deeply searching ability and easily relapsing into local extremum in basic Fruit Fly Optimization Algorithm (FOA), a new algorithm named Shuffled Fruit Fly Optimization Algorithm with Local Deep Search (SFOALDS) was proposed. The local optimal individual in each group was deeply searched circularly by referencing updating strategy of Shuffled Frog Leaping Algorithm (SFLA). SFOALDS not only efficiently avoids relapsing into local extremum, but also improves convergence velocity and convergence precision in the late evolution. The experimental results show that the proposed algorithm has better global searching performance than basic FOA and SFLA, especially on high dimensional functions.

K-means clustering algorithm based on improved artificial bee colony algorithm

YU Jinping ZHENG Jie MEI Hongbiao

2014, 34(4):  1065-1069.  DOI: 10.11772/j.issn.1001-9081.2014.04.1065

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In order to overcome the disadvantages of the K-Means Clustering (KMC) algorithm, such as the poor global search ability, being sensitive to initial cluster centroid, as well as the initial random, being vulnerable to trap in local optima and the slow convergence velocity in later period of the original Artificial Bee Colony (ABC) algorithm, an Improved ABC (IABC) algorithm was proposed. IABC algorithm adopted the max-min distance product algorithm for initial bee colony to form a fitness function, which is adapted to the KMC algorithm, and a position updating method based on the global leading to enhance the efficiency of the iterative optimization process. The combination of the IABC and KMC (IABC-Kmeans) would improve the efficiency of clustering. The simulation experiments were conducted on the four standard test functions including Sphere, Rastrigin, Rosenbrock and Griewank and the UCI standard data sets. The experimental results indicate that IABC algorithm has a fast convergence speed, and overcomes the defect of the original algorithm being easily falling into local optimal solution; IABC-Kmeans has better clustering quality and general performance.

Adaptive range particle swarm optimization with the Cauchy distributed population

LU Shaohua ZHANG Xiaowei BAO Chengqiang LI Wenbao

2014, 34(4):  1070-1073.  DOI: 10.11772/j.issn.1001-9081.2014.04.1070

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In order to improve the performance of the Particle Swarm Optimization (PSO), an adaptive range PSO with the Cauchy distributed population named ARPSO/C was proposed. The algorithm used the median and scale parameters to adjust self-adaptively the search range in population under the suppose of the individuals obeying the Cauchy distribution, thus balanced between local search and global search. The numerical comparison results on the proposed algorithm, ARPSO and PSO show that the presented algorithm has higher convergence speed and can overcome the prematurity.

Multi-objective particle swarm optimization algorithm based on global best position adaptive selection and local search

HUANG Min JIANG Yu MAO An JIANG Qi

2014, 34(4):  1074-1079.  DOI: 10.11772/j.issn.1001-9081.2014.04.1074

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To deal with the problems of the strategies for selecting the global best position and the low local search ability, a multi-objective particle swarm optimization algorithm based on global best position adaptive selection and local search named MOPSO-GL was proposed. During the guiding particles selection in MOPSO-GL, the Sigma method and crowding distance of the particle in the archive were used and the archive member chose the guided particles in the swarm to improve the solution diversity and the swarm uniformity. Therefore, the population might get close to the true Pareto optimal solutions uniformly and quickly. Furthermore, the improved chaotic optimization strategy based on Skew Tent map was adopted, to improve the local search ability and the convergence of MOPSO-GL when the search ability of MOPSO-GL got weak. The simulation results show that MOPSO-GL has better convergence and distribution.

Numerical simulation-based particle swarm optimization algorithm of singularly perturbed reaction-diffusion equation

LIU Libin OUYANG Aijia

2014, 34(4):  1080-1082.  DOI: 10.11772/j.issn.1001-9081.2014.04.1080

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There are some uncertainty defects of parameter selection in excessive grid points, when Shishkin mesh method is used to solve singularly perturbed reaction-diffusion equations by numerical solution. The Particle Swarm Optimization (PSO) algorithm was used to estimate the parameters of Shishkin mesh. First, based on finite difference method, an unconstrained optimization problem which was directed towards minimizing error norm was constructed. Then the PSO was used to solve it. The proposed method overcame the defects of artificial parameters selection. The experimental results show that compared with the simplex algorithm, PSO can converge to the global optimal solution for optimizing the parameters of Shishkin mesh. The accuracy of numerical computing is improved significantly for singularly perturbed reaction-diffusion equations on the boundary layer, which further illustrates the effectiveness and feasibility of the proposed method.

Structure learning algorithm for general multi-dimensional Bayesian network classifiers

FU Shunkai SEIN Minn LI Zhiqiang

2014, 34(4):  1083-1088.  DOI: 10.11772/j.issn.1001-9081.2014.04.1083

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The conventional Multi-dimensional Bayesian Network Classifier (MBNC) requires its structure be bi-partitie. Removing this constraint can result into a new tool named General MBNC (GMBNC), and it enables us to model the underlying joint distribution more correctly. Based on iterative local search of Markov blankets, an algorithm called IPC-GMBNC was proposed to induce the exact structure of GMBNC. The proposed algorithm has good scalability because it does not need to recover the global Bayesian Network (BN) first. The experiments on samples generated from known Bayesian network structures indicate that IPC-GMBNC is effective, and it brings great reduction on computing complexity compared to global search approach, e.g. PC algorithm.

Ensemble Extreme Learning Machine Based on the Members Similarity

YE Songlin HAN Fei ZHAO Minru

2014, 34(4):  1089-1093.  DOI: 10.11772/j.issn.1001-9081.2014.04.1089

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To increase the diversity among the selected members to enhance the performance of the ensemble system, an ensemble Extreme Learning Machine (ELM) based on the selection of members similarity named EELMBSMS was proposed. Firstly, some candidate ELMs with high classification ability were selected. Then, Particle Swarm Optimization (PSO) algorithm was used to select the optimal subset of the ensemble members according to the similarity among the members. The diversity of the selected members was improved by selecting those ELMs with low similarity, which improved the classification performance of the ensemble system effectively. The selected ELMs obtained better performance with different integration rules. The experimental results on four UCI datasets verify that EELMBSMS has better stability and better generalization than some classical ensemble extreme learning machines.

Self-adaptive learning algorithm for collaborative representation classification of multi-feature elements

WANG Jianren WEI Long DUAN Ganglong HUANG Tiyun

2014, 34(4):  1094-1098.  DOI: 10.11772/j.issn.1001-9081.2014.04.1094

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To address the weak discriminative power of Sparse Representation Classification (SRC), a self-adaptive learning algorithm for collaborative representation classification of multi-feature elements named SLMCE_CRC was proposed. Based on the idea of multi-feature sub-dictionary, the sample was collaboratively represented by features and elements, the sparse weights of features and the residual weights of elements were learnd self-adaptively and combined linearly to classify the samples. The experimental results demonstrate the effectiveness and high classification accuracy of the proposed algorithm. It is suitable to images with multi-features.

Appraisal expression recognition based on Tri-training

JIANG Run GU Chunhua RUAN Tong

2014, 34(4):  1099-1104.  DOI: 10.11772/j.issn.1001-9081.2014.04.1099

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Appraisal expression recognition is very important in sentiment analysis. Because of the lack of labeled corpus, most former works in appraisal expression recognition are focused on construction of rules and templates manually. In order to reduce the training work of labeling corpus and further mining information of unlabeled corpus, a new algorithm based on co-training was proposed, which mainly used massive unlabeled corpus and only a small number of labeled corpus. The proposed algorithm was based on Tri-training and combined Support Vector Machine (SVM), Maximum Entropy (MaxEnt) and Conditional Random Field (CRF) to build a new approach for candidate appraisal expression classification. By comparing the Tri-training based algorithm with the former single classifier based algorithms, the former can effectively improve the performance of appraisal expression recognition in subjective sentences.

Modeling of marine ecology ontology

YUN Hongyan XU Liangjian GUO Zhenbo WEI Xiaoyan

2014, 34(4):  1105-1108.  DOI: 10.11772/j.issn.1001-9081.2014.04.1105

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According to characters of marine ecology domain knowledge, a marine ecology knowledge organization model was proposed. Referring to engineering field literature and the device-function knowledge representation theory that the "function" concept was used to describe marine ecology functional process; a viewpoint of device-function was fixed, a domain upper ontology for marine ecosystem was presented, and then marine ecological conceptual model and marine ecology OWL ontology were constructed. By extending OWL-DL, OWL-Process model oriented function-process was proposed, and then marine ecology function-process ontology instance was constructed. Based on constructed marine ecology ontology repository, marine ecological knowledge management system was developed. The ontology application system provides marine ecology knowledge query and crisis early warning functions; and it also verifies the validity, rationality and feasibility of constructed marine ecology ontology.

Chinese phrase parsing with semantic information

GENG Lifei LI Honglian LYU Xueqiang WU Yunfang

2014, 34(4):  1109-1113.  DOI: 10.11772/j.issn.1001-9081.2014.04.1109

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To deal with the poor performance of word sense disambiguation in parsing, a Chinese phrase parsing approach was proposed based on disambiguation of Chinese part of speech. First, it expanded part of speech of TongYiCi CiLin and then substituted the original words in the training set and test set with semantics codes. In this process, it used part of speech of word for word sense disambiguation. The experimental results on Penn Chinese TreeBank (CTB) show that the proposed method achieves precision rate of 80.30%, recall rate of 78.12%, and F-measure of 79.19%. Relative to the no disambiguation system, the presented approach can effectively improve the performance of phrase parsing.

Personalized recommendation algorithm integrating roulette walk and combined time effect

ZHAO Ting XIAO Ruliang SUN Cong CHEN Hongtao LI Yuanxin LI Hongen

2014, 34(4):  1114-1117.  DOI: 10.11772/j.issn.1001-9081.2014.04.1114

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The traditional graph-based recommendation algorithm neglects the combined time factor which results in the poor recommendation quality. In order to solve this problem, a personalized recommendation algorithm integrating roulette walk and combined time effect was proposed. Based on the user-item bipartite graph, the algorithm introduced attenuation function to quantize combined time factor as association probability of the nodes; Then roulette selection model was utilized to select the next target node according to those associated probability of the nodes skillfully; Finally, the top-N recommendation for each user was provided. The experimental results show that the improved algorithm is better in terms of precision, recall and coverage index, compared with the conventional PersonalRank random-walk algorithm.

Multi-Agent cooperative E-commerce recommender system model

WEI Shimin DAI Duhong

2014, 34(4):  1118-1121.  DOI: 10.11772/j.issn.1001-9081.2014.04.1118

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In order to further improve the accuracy and efficiency of product recommendation in E-commerce recommender system, by analyzing the problems of traditional recommender system and prior optimization technique, a multi-Agent recommender system model was proposed. By adopting multi-Agent technique in Artificial Intelligence (AI) and terminal self-adaption, this model improved the efficiency of traditional recommender system in the condition of using multi-terminal, and dynamically returned recommendation to users according to different terminals. The experimental results show that multi-Agent cooperative E-commerce recommender system improves the accuracy and efficiency to a certain extent.

Application of deep belief nets in spam filtering

SUN Jingguang JIANG Jinye MENG Xiangfu LI Xiujuan

2014, 34(4):  1122-1125.  DOI: 10.11772/j.issn.1001-9081.2014.04.1122

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Concerning the problem that how to initialize the weights of deep neural networks, which resulted in poor solutions with low generalization for spam filtering, a classification method of Deep Belief Net (DBN) was proposed based on the fact that the existing spam classifications are shallow learning methods. The DBN was pre-trained with the greedy layer-wise unsupervised algorithm, which achieved the initialization of the network. The experiments were conducted on three datesets named LinsSpam, SpamAssassin and Enron1. It is shown that compared with Support Vector Machines (SVM) which is the state-of-the-art method for spam filtering in terms of classification performance, the spam filtering using DBN is feasible, and can get better accuracy and recall.

Object detection method of few samples based on two-stage voting

XU Pei ZHAO Xuezhuan TANG Hongqiang ZHAN Weipeng

2014, 34(4):  1126-1129.  DOI: 10.11772/j.issn.1001-9081.2014.04.1126

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A method of object detection with few samples based on two-stage voting was proposed to detect objects using template matching method while there are only a few samples. Firstly, the voting space was constructed off-line by using probability model through several samples. Then, a method of two-stage voting was used to detect objects in testing images. In the first stage, the components of object from testing image were detected, and the positions of components in query image were saved. In the second stage, the similarity of the object was computed integrally based on the components. According to the theory analysis and experimental results, the proposed method obtains lower computation complexity and higher precisions than previous works.

Skin-color detection algorithm with strong robustness in illumination

HUANG Tinghui YANG Fei CUI Gengshen

2014, 34(4):  1130-1133.  DOI: 10.11772/j.issn.1001-9081.2014.04.1133

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According to the fact that the performance of skin-color detection is greatly affected by the illumination, a kind of skin-color detection algorithm with good stability was proposed. According to the characteristic of face symmetry, the pixel correction algorithm was used to replace too bright or too dark pixels on the face area with normal ones, and then an adaptive method was used for skin-color detection, in which the corresponding chroma threshold was determined dynamically by the brightness of pixel. The experimental results show that, compared to other algorithms such as the YCbCr single Gauss model for skin-color detection, more than 10% of positive detection rate was increased and the false positive rate was reduced by 5% with the proposed algorithm under different light intensity. Moreover, the stability of the proposed algorithm is significantly enhanced.

Facial expression recognition based on Gabor Parameters Matrix and improved Adaboost

YANG Fan ZHANG Lei

2014, 34(4):  1134-1138.  DOI: 10.11772/j.issn.1001-9081.2014.04.1134

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To solve the problems of high-dimensionality, giant-computation and redundancy of Gabor features in current Facial Expression Recognition (FER), a new FER algorithm based on Gabor Parameter Matrix (GPM) and improved Adaboost was proposed. Firstly, the GPM was defined by combining pixel information of image and parameters of Gabor wavelet kernel; Secondly, the idea of Genetic Algorithm (GA) was introduced into Adaboost to improve its searching performance, then the improved Adaboost was used to select optimal features corresponding to the elements in GPM to build strong classifiers, thereby the dimensionalities, redundancy and calculation amount of Gabor features could be reduced by feature selection; Finally, on the basis of building several strong classifiers, a multi-expressions classification algorithm was developed to implement FER. The experimental results on Matlab indicate that average expression recognition rate of the proposed algorithm is 89.67%, and the selection efficiency of optimal features is improved significantly.

Extension of contradiction problem-oriented description logic SHOQ

WANG Jing WANG Hong LI Jian FAN Hongjie

2014, 34(4):  1139-1143.  DOI: 10.11772/j.issn.1001-9081.2014.04.1139

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In order to apply reasoning rules of the description logic to analyze and solve the simple contradiction problem, the extension set was introduced to be the set theory foundation of the description logic SHOQ, and a new description logic named D-SHOQES (Dynamic Description Logic SHOQ Based on Extension Set) was proposed. The cut sets of extension concepts and extension roles were defined as atomic concepts and atomic roles, and the action theory was injected to obtain the qualitative change domain and the quantitative change domain of the concepts and roles. The semantics of concepts, roles and actions in D-SHOQES were given, as well as the Tableau-algorithm reasoning rules. Finally, the method of solving contradiction problem was researched, which offered a strategy for the solution to contradiction problem.

Inverse reasoning of 3D cardinal direction relations based on block algebra

WANG Miao HUANG Zhiguo LI Song

2014, 34(4):  1144-1148.  DOI: 10.11772/j.issn.1001-9081.2014.04.1144

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In order to enrich and improve the ability of the existing models for reasoning and predicting with 3D cardinal direction relations and enhance the usability of the existing models, and then better meet the demands of real applications for complex 3D spatial data, the inverse reasoning of 3D cardinal direction relations was studied. After deeply studying the theory of n-dimensional block algebra, an algorithm for computing the inverse of the basic 3D cardinal direction relations on the basis of 3D block algebra was devised. Theoretical analysis and the results of the example show that the proposed algorithm is correct and complete. This work can better enhance the power of intelligent analysis and processing for the complex 3D direction relations of the spatial database.

Dynamic and self-adaptive middleware infrastructure for supporting context-aware applications

XU Nan ZHANG Weishi

2014, 34(4):  1149-1154.  DOI: 10.11772/j.issn.1001-9081.2014.04.1149

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Context-aware computing is one of the indispendable key technologies for developing and deploying intelligent applications. Whether the context can really contribute to the applications mainly depends on the following two aspects: the first is how to continuously and steadily monitor/capture high-quality context information from the dynamic interaction environment, the second is how to reason on contexts and make adaptation decisions for applications. A layered middleware infrastructure was designed to achieve the above objectives. It afforded effective supports for not only gathering, managing, interpreting and making use of context information to dynamically adapt applications, but also selecting the most appropriate context sources dynamically at runtime based upon Qualities of Context (QoC). Finally, the experimental results show that the middleware can quickly and efficiently support the development and deployment of context-aware applications, and has better computing performance in comparison with others.

Extending UML use case for software fuzzy self-adaptation

HAN Deshuai XING Jianchun YAGN Qiliang

2014, 34(4):  1155-1160.  DOI: 10.11772/j.issn.1001-9081.2014.04.1155

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The standard Unified Modeling Language (UML) and general tools for self-adaptive software could not model Software Fuzzy Self-Adaptation (SFSA) directly in the analysis and design phases. A new approach called Fuzzy Case was proposed by extending UML use case for the modeling of SFSA. By combining the conceptual framework of SFSA and applying the UML extending mechanism, new stereotypes and tagged values were introduced and a meta-model for Fuzzy Case was created. Then, the syntax structure was given and the semantics of Fuzzy Case were defined with Object Constraint Language (OCL). The instance validation shows that, compared with the traditional approaches, Fuzzy Case can express structures of SFSA more explicitly, define semantics of SFSA more accurately and model SFSA more conveniently. The proposed approach plays an important role in improving the development efficiency of SFSA.

Model driven transformation from UML model to the N-layer Web model

SU Hongjun YAN Yunshan YOU Zhenhua

2014, 34(4):  1161-1164.  DOI: 10.11772/j.issn.1001-9081.2014.04.1161

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Model Driven Architecture (MDA) refers to the method and standard system for the application of model technology in software development proposed by Object Management Group (OMG), the core idea of which includes the modeling of platform-independent model and the transformation of platform-specific model. The framework was realized by programming based on Meta Object Facility 2.0 (MOF2.0) Query/View/Transformation (QVT) standard definition, and it could achieve transformation of meta model to specific N-layer application class and realize main functions of the program, thus greatly improving the development efficiency. The flexibility of model-driven transformation and diversity of function realization achieved by programming were verified, including the description of model specification by XML documents and the integrity of code generation

Research on data model of remote sensing image template based on partition theory

DU Genyuan XIONG Delan ZHANG Huolin

2014, 34(4):  1165-1168.  DOI: 10.11772/j.issn.1001-9081.2014.04.1165

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With the increasing amount of data and expanding of application demand, the efficient organizational management and rapid processing speed of remote sensing data have become a bottleneck in the application of remote sensing technology. The earth partition theory and high performance computing provide a possible way to solve the above problem. Combined with global partition model, the conceptual model and data model of partition facet template were proposed based on partition facet of remote sensing image. A computing mode of partition facets based on templates was designed, and a small partition template database was established. A specific example of partition image data template applications was also given for validation. The experimental results demonstrate the feasibility of the data model and improve the efficiency of targets retrieval.

Cross-domain active learning algorithm for image classification

SHAO Xin

2014, 34(4):  1169-1171.  DOI: 10.11772/j.issn.1001-9081.2014.04.1169

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To solve the problem of ignoring common information in different domains in traditional active learning image classification, a new multi-domain active learning image classification method was proposed to reduce the labeling effort of image classification. It learned a subspace to represent common features among different images. Considering the common features and domain-specific features, the model loss due to each data instance could be divided into two parts, so that the common information could be queried from the common part. The experimental results show that the new method has some precise increase and has 30% less labeling efforts than the single model method and mixture model method. The results reveal that the new method can be widely used in all kinds of image classification tasks with higher precise and efficiency.

Visual vocabulary with weighted feature space information based image retrieval model

DONG Jian

2014, 34(4):  1172-1176.  DOI: 10.11772/j.issn.1001-9081.2014.04.1172

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Concerning the quantization error when the local features were quantified by the visual vocabulary in traditional Bag-of-Visual-Word (BoVW) model, an image retrieval model based on visual vocabulary with weighted feature space information was proposed. Considered the clustering method which was used to generate the visual codebook, the statistic information of the feature space was analyzed during the clustering process. Through the comparison of different weighting methods by experiments, the best weighting method, mean weighted average, was found to weight the visual words to improve the descriptive ability of the codebook. The experiment on ImageNet dataset shows that, compared to homologous visual codebook, non-homologous visual codebook has less impact on dividing the visual space, and the effects of the weighted feature space based visual codebook on big dataset are better.

Defocus blur parameter estimation method based on blur spectrum characteristic of image edge

LIANG Min ZHU Hong

2014, 34(4):  1177-1181.  DOI: 10.11772/j.issn.1001-9081.2014.04.1177

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The accurate estimation of the Point Spread Function (PSF) is the key point in image restoration. For the unknown PSF parameter of defocus blur, an estimation method was proposed based on blur spectrum characteristic of image edge. Specifically, the blur spectrum feature of basic edge was analyzed, and then the edge model of natural image was treated as reference image. Furthermore, the max spectrum similarity was analyzed to obtain the right parameter between the image to be restored and the blurred reference image with defocus parameter in a continuous range. The experimental results show that the proposed algorithm suits large scale defocus blur images and has strong anti-noise ability.

Super resolution image reconstruction based on wavelet transform and non-local means

YE Shuangqing YANG Xiaomei

2014, 34(4):  1182-1186.  DOI: 10.11772/j.issn.1001-9081.2014.04.1182

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Combining Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT) and Non-Local Means (NLM), a new single-frame Super-Resolution (SR) method named DSNLM was proposed to eliminate the blurring effect in wavelet domain SR image. In DSNLM, the subbands were obtained by applying DWT to low-resolution input image, and SWT was simultaneously applied to obtain high frequency subbands; Then NLM filter was applied to these composite subbands along with the interpolated input image. Finally, Inverse Discrete Wavelet Transform (IDWT) was applied to these subbands to obtain the SR image. The experimental and visual results verify the superiority of the proposed method over the conventional image resolution enhancement techniques with improved Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE) and Structural SIMilarity (SSIM), and it is effective in denoising and blurring.

Detail-preserving hierarchical tone-mapping algorithm for high dynamic range images

WEI Chunao XIE Dehong WANG Qi LI Rui

2014, 34(4):  1187-1191.  DOI: 10.11772/j.issn.1001-9081.2014.04.1187

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Due to problems of over-compression by a non-adaptive mapping function, and changes of perceived contrasts for luminance shift during mapping, a hierarchical tone-mapping algorithm for detail-preserving was proposed. In this algorithm, the luminance-response curve adapting to each local luminance in High Dynamic Range (HDR) images, as a mapping function, was used to map luminances of the base layer. Then, compensation coefficients of the detail layer, for stretching or compressing details, were computed according to values of luminance shift based on Stevens' effect. The experimental results show that the proposed algorithm has good performance on preserving perceived details.

Improvement and simulation of K-shortest-paths algorithm in international flight route network

HU Xin XU Tao DING Xialu LI Jianfu

2014, 34(4):  1192-1195.  DOI: 10.11772/j.issn.1001-9081.2014.04.1192

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K-Shortest-Paths (KSP) problem is the optimization issue in international flight route network. With the analysis on the international flight route network and KSP algorithm, the typical Yen algorithm solve KSP problem was investigated. To resolve the problem that Yen algorithm occupied much time in solving the candidate paths, an improved Yen algorithm was proposed. The improved Yen algorithm was set up by using the heuristic strategy of A* algorithm, which reduced the time to generate candidate paths, thereby, the search efficiency was improved and the search scale was reduced. The simulation results of international flight route network example show that the improved Yen algorithm can quickly solve KSP problem in international flight route network. Compared with the Yen algorithm, the efficiency of the proposed algorithm is increased by 75.19%, so it can provide decision support for international flight route optimization.

Pre-positioning facilities for collecting tents from communities in post-earthquake relief

ZHOU Jingxian HU Zhihua ZHANG Mengjun

2014, 34(4):  1196-1200.  DOI: 10.11772/j.issn.1001-9081.2014.04.1196

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Pre-positioning facilities for collecting tents held by communities is helpful to improve the efficacy of tents collection in post-earthquake relief. A problem for pre-positioning facilities that collect the tents held by commnities considering various earthquake scenarios was studied. A bi-stage stochastic programming model was formulated for the facility location problem. The model aimed at minimizing economic costs and time-related costs. Considering the effects of weights and other parameters on the solutions, five experiments were performed and analyzed. A case was used to verify the practicability of the developed model that located the facilities of tents collection from communities in Pudong New District, Shanghai. Finally, a scenario based on Ya'an earthquake was used to analyze the influence of parameters on the solution under such a certain scenario.

Equipment system availability analysis and project optimization based on cannibalization

BAO Jikai LUO Changyuan ZHOU Daoshui LI

2014, 34(4):  1201-1204.  DOI: 10.11772/j.issn.1001-9081.2014.04.1201

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First, the maintenance spare parts supply process of a two-echelon support system under cannibalization was studied, and the system availabilities under three strategies including non-cannibalization strategy, cannibalization strategy and partial cannibalization strategy were analyzed. Based on this, the inventory optimization model was established. The system availability was used as the constraint while the minimize support costs were taken as optimization objective, and the marginal analysis method was selected to solve the model. The results by comparing to different strategies indicate that taking cannibalization strategy can reduce inventory and total costs under minimum availability, and can effectively improve equipment availability under certain inventory.

Inertial navigation scheme for industrial mobile robot with local precise positioning

GUAN Linbo DONG Lida YI Jun

2014, 34(4):  1205-1208.  DOI: 10.11772/j.issn.1001-9081.2014.04.1205

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In order to solve the problem of complexity for laying the ground magnetic, laser reflection point or other devices before industrial mobile robot can come into service, and the inflexibility resulting from the fixed work path, a scheme of industrial mobile robot navigation based on inertial and ultrasonic sensors was proposed. Operator needed to train the robot from one target position moving towards another target position in advance to acquire train path. When the robot worked in non-target area, i.e. the area demanding low location accuracy, it navigated according to the train path based on inertial sensors; When coming into target area, i.e. the area containing target position and demanding high location accuracy, ultrasonic sensors conducted the navigation. The scheme shortened the preparation period, and it was convenient to change work path. The simulation results show that the scheme combining inertial navigation and ultrasonic location is feasible.

Mobile robot safety navigation based on time to contact

HAO Dapeng FU Weiping WANG Wen

2014, 34(4):  1209-1212.  DOI: 10.11772/j.issn.1001-9081.2014.04.1209

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Navigation exists potential safety hazard when autonomous mobile robot moves in dynamic uncertain environments. In order to improve the navigation safety, a representation method of navigation environments using time of contact was proposed, namely time of contact space. As risk index in navigation environments, the time of contact between two points of an arbitrary was computed by using linear velocity and rotation velocity, and the configuration space was mapped into time of contact space when robot moved in the navigation environment. The time of contact space was applied to classic behavior dynamic navigation method. Compared with the classical behavior dynamics method and behavior dynamics adding velocity obstacles, the simulation results prove that the time of contact space can guarantee safety navigation of autonomous mobile robot.

Simulation on low speed stable operation of full-order observer for induction motor

LI Hongbo JIANG Lin WANG Haitang

2014, 34(4):  1213-1216.  DOI: 10.11772/j.issn.1001-9081.2014.04.1213

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For the low-speed instability problem of speed sensor-less vector control system of induction motor based on full-order flux observer, the unstable reason of observer at the low-speed generation region was analyzed by applying Popov's hyperstability theory, and a design criteria of feedback gain was proposed to stabilize the observer at low-speed mode. A stability analysis process was simplified based on rotor flux orientation and a multi-dimensional problem about the system poles stability was transformed into a one-dimensional problem about system zeros stability by using Routh-Hurwitz criterion. Furthermore, the stability condition of speed estimation system was derived and a design method of stability feedback gain was obtained. The simulation results show that the speed estimation system can work stably at a low speed of 50 revolutions per minute and a very low speed of 10 revolutions per minute. Compared with the traditional poles assignment approach, the system has better convergence and stability performance at low-speed generation region, and improves the dynamic and static performances of speed sensor-less vector control system at low-speed region.

Energy consumption estimation modeling of aluminum hydroxide gas suspension calcinations based on least squares support vector machine and genetic algorithm

LIU Daifei YI Ji DING Fengqi

2014, 34(4):  1217-1221.  DOI: 10.11772/j.issn.1001-9081.2014.04.1217

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According to the requirement of energy consumption information representation and model application in aluminum hydroxide gas suspension calcinations process, a kind of energy consumption estimation model was established based on Least Squares Support Vector Machine (LS-SVM) method. By combining the energy consumption model with Genetic Algorithm (GA), a kind of parameters optimization and industry application strategy was presented. Input parameters of energy estimation model were analyzed through grey relational analysis method, and the main factors of input parameters consisted of main furnace temperature, oxygen content of exhaust gas and containing water of aluminum hydroxide. The sampled data of energy consumption parameters were regrouped and optimized through K-fold cross-validation method. By comparing prediction accuracy of energy consumption models with various kernel functions, Radial Basis Function (RBF) kernel function was adopted to express feature information of sampling data. A model switcher whose inputs were energy parameters and output was symbol parameter of energy estimation model was constructed by Support Vector Machines (SVM) method. Self-learning and dynamic optimization processes of energy estimation model were realized by sample data updating and clustering. Model selection and application were realized by using the model switcher according to various calcinations conditions. The experimental results show that the LS-SVM modeling and application strategy can improve the generalization capability and conditions adaptability of energy estimation model. The presented strategy of model application is a feasible method for energy parameter analysis and estimation.

Design of universal embedded serial time codes acquisition system

DUAN Xiaohu CUI Shuang

2014, 34(4):  1222-1226.  DOI: 10.11772/j.issn.1001-9081.2014.04.1226

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The acquisition and processing of time information plays a key role in the modern electronic computing systems. Due to the poor hardware compatibility of the other time code acquisition systems caused by the varied formats of InterRange Instrumentation Group (IRIG) serial time code, a universal IRIG serial time code acquisition and analysis system compatible with different formats was designed. The acquisition system adopted hardware and software hierarchical analysis methods to achieve universal treatment of various IRIG codes, and used internal counters, timers and other means to improve the system's hardware timing accuracy, instantaneity, and fault tolerance. The application results show that compared with other IRIG code acquisition circuits, this system has great improvement on universality and scalability, and the timing accuracy is increased from second and millisecond level to nanosecond level. The system is applicable to different embedded applications of time information collection and real-time processing needs.