Abstract:Construction and evolution are two basic properties of software. Software evolution consists of a series of complex change activities. Software complexity decides that the research of software evolution should start with the macroscopical level firstly. Software architecture (SA), which acts as a blueprint and a skeleton of software, offers an availability approach with the whole macroscopical software architecture and evolution grasped by people. The component, connector models, which create SA relation matrix and reachability matrix, are described. Depending on matrix shift and calculation, ripple-effect of SA evolution can be analyzed and its quantity can be ascertained, describing every ripple-effect caused by component deletion, addition, modification, division and combination respectively. At the same time, an approach for calculating the relative quantity of component effect is described. All are credible foundation for management, control, usage and evaluation of SA evolution, and are foundation for SA evolution automation calculation based on matrix shift in computer.

Abstract:The LSF (least slack first) algorithm assigns a priority to a task according to its executing urgency. The smaller the remaining slack time of a task is, the sooner it needs to be executed. However, LSF may frequently cause switching or serious thrashing among tasks, which augments the overhead of a system and restricts its application. Assigning a preemption threshold in the scheduling policy can decrease the switching among tasks, however, the existing assigning methods are limited to the fixed priority such that they are not applied to the LSF algorithm. In order to relieve the thrashing caused by LSF, some applicable assigning schemes are presented to the LSF algorithm based on the preemption threshold. Every task is dynamically assigned a preemption threshold that is dynamically changing with the executing urgency of the task and is not limited by the number of tasks. Simulations show that, by using the improved LSF policy, the switching among tasks decreases greatly while the missed deadline percentage decreases. The proposed algorithm is useful for designing and implementing a real-time operating system.

Abstract:The redundant data in log files and the delay for detecting abnormal trails are the inherent problems existing in the traditional secure monitoring subsystem of a computer system. In this paper, it is identified that the system security policies determine the logging data items in a secure monitoring function. By formally describing and analyzing the famous Clark-Wilson integrity policies with the corresponding relation patterns, the minimal logging data items set involved in these security policies is precisely determined. A formal secure monitoring model based on Clark-Wilson integrity policies (CW-SMM) is proposed. The CW-SMM has the characteristics of both minimal logging data and auto-detecting of the system abnormal trails in time, and can thoroughly solve the problems mentioned above.

Abstract:Collaborative editing systems support a group of collaborators to edit or view the same graphics at the same time from geographically dispersed sites connected by communication networks. The research on this is of great challenge. The multi-versioning technique in collaborative graphics editing system is discussed. This paper puts emphasis on object identification and its strategies, some existing problems. A general object identification solution for these problems is proposed, which solves their object identification and system maintenance between operations with causality relationships, and with identical relationships, that the existing strategies cannot resolve. On the other hand, the size of object identification will become larger and larger with the progress of collaborative editing works and the generation of conflicting operations, thus affect the efficiency of the system. Therefore, some rules suitable to the compression of the object identification is analyzed, an object compression method is presented and its validity is also analyzed. Analysis of some examples and experimental results show that all strategies and algorithms presented in this paper improve the efficiency of the system.

Abstract:Temporal and spatial reasonings are two important parts of Artificial Intelligence and they have important applications in the fields of GIS (geographic information system), Spatio-temporal Database, CAD/CAM etc. The development of temporal reasoning and spatial reasoning is discussed from three aspects: Ontology, representation model and reasoning methods, and the research progress of spatio-temporal reasoning is summarized. The problems of current research are discussed and the future directions are pointed out.

Abstract:The combination of conflicting evidences has been one of the important issues in Dempster-Shafer theory since the example of Zadeh paradox produced by Dempsters rule of combination was found. There is no solution accepted universally as yet. In this paper, an approach to handling this problem is proposed. Before adopting the Dempsters rule to combine belief functions, the assignments of mass functions are pretreated by the disturbance of ignorance. The pretreatment is in favor of the normalization of combination. Compared with other alternatives, the new approach is consistent with Dempsters rule in the form and flexible to combination, especially, it can be theoretically explained by the generalized Bayesian formula.

Abstract:The object-oriented method is passive, so it is not consistent with the active rules and can not easily define the functions and features of the objects in a distributed and active database system. And also the active rules lead to the problems of termination and confluence. In this paper, the Agent method, distributed database, and active database are combined after the constraints of the object-oriented method are analyzed. On the basis of the combination, a distributed and active database system framework based on the Agent-oriented method is proposed. As to the system framework, a method of expanding the event-rule graph and an improved Coffman-Graham parallel algorithm are presented, and then their performances are analyzed. Shown by the analysis results, the former is used to solve the problem of database system termination, while the latter, on the foundation of remaining the confluence, improves the efficiency of parallel rule process. Besides, the database system framework is useful for applying the Agent method to the distributed and active database.

Abstract:There is a lot of redundant information in a data cube. Removing redundancy from a data cube can not only reduce the storage space but also accelerate the computation. Tuples of a data cube can be divided into closed-tuples and non-closed tuples. For any non-closed tuple, there exists a closed-tuple, and both are aggregated from the same set of tuples in a base table and have the same aggregated value. By removing all non-closed tuples, a data cube can be translated to a closed data cube. The algorithm of computing a closed data cube is given, answering a query and maintaining the closed data cube incrementally. The results of experiments are also presented by using both the synthetic and real-world data sets. The experimental results show that the closed data cube technique is effective.

Abstract:The study on streaming data is one of the hot topics among the database circle all over the world recently. During the past three decades, conventional database technologies have been well developed and widely applied. Unfortunately, they could not be adopted to handle a new kind of data, named streaming data, which is generated from applications such as network routing, sensor networking, stock analysis, etc. Because of the rapid data arriving speed and huge size of data set in stream model, novel algorithms that only require seeing the whole data set once are devised to support aggregation queries on demand. In addition, this kind of algorithms usually owns a data structure far smaller than the size of the whole data set. The ways to devise such synopsis data structures are introduced. These different approaches are also compared by listing historical works upon two classical problems over stream.

Abstract:To improve quality of personalized recommendation and simplify the preference setup in generating recommendation rules, the characteristics of the association rule for personalized recommendation are discussed, the concepts of recommendation nonblank metric, a new recommendation metric, 1-support frequent itemset and k-maximal association rule are defined, and the idea of getting k-maximal association rule from 1-support frequent itemset is proposed. Moreover, an association rule mining algorithm based on the idea is designed, which is suitable for different sliding window depths. The theoretic analysis and experiment results on the algorithm show that the method has maximal nonblank, higher precision and F-measure of recommendation, and simplifies the preference setup of thresholds in mining rules effectively.

Abstract:The incremental updating research of frequent itemsets is an important data mining problem in data mining fields. Many sequential algorithms have been proposed for incremental updating of frequent itemsets. However, very little work has been done in updating frequent itemsets in distributed environment. In this paper, the algorithm FUAGFI (fast updating algorithm for globally frequent itemsets) is introduced in the case of inserting, which efficiently utilizes the created locally frequent pattern trees and the mined globally frequent itemsets. Therefore, FUAGFI uses far less communication overhead and obviously improves updating efficiency of globally frequent itemsets. Experimental results show the feasibility and effectiveness of the algorithm.

Abstract:This paper integrates the advantage of the FP-Tree algorithm for mining association rules and the maximum clique theory of graph. The main contributions include: (1) An improved method to mine frequent 2-itemset by adjacency matrix is proposed. (2) The concept of maximum ordered frequent itemset is proposed, and the equivalence of Head Relation is proved as along with the theorems about Local Complexity and Merge Convergence Range. (3) The MaxCFPTree algorithm based on Maximum-clique partition is proposed and implemented with complexity O(n²). (4) The algorithms are validated by extensive experiments. The conflict between memory and huge number of items is resolved, and the system efficiency and scalability are improved.

Abstract:With the explosive growth of network applications and complexity, the threat of Internet worms against network security becomes increasingly serious. Especially under the environment of Internet, the variety of the propagation ways and the complexity of the application environment result in worm with much higher frequency of outbreak, much deeper latency and more wider coverage, and Internet worms have been a primary issue faced by malicious code researchers. In this paper, the concept and research situation of Internet worms, exploration function component and execution mechanism are first presented, then the scanning strategies and propagation model are discussed, and finally the critical techniques of Internet worm prevention are given. Some major problems and research trends in this area are also addressed.

Abstract:As the basis of Internet development and exploitation on higher levels, the Internet topology modeling starts from the random model to the hierarchical model. Then it developed to a more realistic one, scale-free network model. Many characteristics of topology are analyzed with the corresponding metrics, including power law. Moreover, the related work on the current topology models, topology generation algorithms, and topology generators is fully presented. Finally, the new problems and challenges which arise from current research are discussed and some suggestions for future research work are put forward.

Abstract:Sampling methodologies are widely used in network measurements and other related fields. Most applications mainly focus on parent population statistical metrics estimation of interest. Recent researches reveal that many aspects of network characters present heavy-tailed distribution or self-similarity. These properties might cause a heavy passive effect on the estimation accuracy. In other circumstances, there exist demands on modeling the characteristics of a network in network operation. To develop an accurate model for network character is much difficult. From a broader view, these applications are treated as special cases of fitting problems of planar data set or time series in applied mathematics. In the paper, a Fitting-based adaptive sampling methodology (FASM) is developed for reconstructing the evolution of some network characteristics (model). The contributions of the paper include: (1) Adopting a Piecewise Linear Function Approximation scheme to provide a more accurate approximation of the true character. (2) The statistical metric derived from the FASM provides a much more stable and accurate estimation than other popular methodologies under the same sampling size. Experiments based on two measurement traces show that the FASM can dramatically reduce the number of samples while retaining the same approximating residual error as others. (3) The variance of sampling size is more stable than those of other probability sampling schemes.

Abstract:In order to determine an optimal route, network performance and cost of many network providers must be compared when end-users visit the content provided by content providers under certain QoS constraints in multi-provider network. The correlative network information is collected by mobile Agent. The delay and cost between any two nodes of network is set to random variables. A minimum model with the expectation of cost and delay value is presented in a stochastic network. The optimal solution of the mobile Agent route from a service provider to a content provider is computed by using genetic algorithms. The obtained simulation results show the effectiveness of the above approach.

Abstract:A new robust public watermarking algorithm in DCT (discrete cosine transform) domain is presented. Due to good randomness and easy reproducibility of chaos, the watermark is firstly permuted by the hashed chaotic sequence, then a small number of reference points are randomly selected in the middle frequency bands of the DCT domain based on the chaotic sequences, and the batch-type disorder watermark bits are embedded into the neighborhood of every reference point using odd-even quantization. The usefulness of multilevel chaotic keys and privacy of modification to frequency coefficients enhance the security of watermark information. The blind extraction of watermarking information is realized under guaranteeing that a larger capacity and significant binary watermark is hidden. Moreover, a reasonable trade-off between the invisibility and robustness is obtained.

Abstract:Watermarking technique is a method by hiding copyright information into covering signals to discourage unauthorized copying. Because the profiles of two-dimension Gabor base functions are similar to those of human visual cortical cell receptive field and the middle frequency of visual channels has octave relationship, a video watermarking algorithm is proposed based on spatio-temporal multi-channel model using 3D Gabor transform in this paper. Experimental results indicate that the Gabor domain watermarks have greater robustness and imperceptibility.

Abstract:Trojan horse attacking strategy on quantum cryptography is investigated. First, the fragility of the quantum cryptographic algorithm employing EPR (Einstein-Podosky-Rosen) pairs as a key against the Trojan horse attacking strategy is analyzed. To prevent the Trojan horse attacking, an improved scheme which makes use of the non-orthogonal entangled states is proposed. This scheme is robust to the Trojan horse attacking, without reducing the security on other kinds of attacking strategies.