Abstract:Based on the current research on the dynamic requirement traceability (DRT), this paper investigates the trace precision problem in depth and proposes a solution—dynamic requirement traceability framework. This framework focuses on automatically establishing traces and combines the traditional requirement traceability activities with change proposal, impact analysis and change control, etc. It makes full use of the characteristics of artifacts and evolutional information of change in the iteration process so as to help establish the requirement traces with higher precision.

Abstract:Definition of view selection issue in the field of data warehouses is presented, followed by the discussion of related problems, such as cost model, benefit function, cost computation, restriction condition, view index, etc. Then three categories of view selection methods, namely, static, dynamic and hybrid methods are discussed. For each method, some representative work is introduced. Finally some future trends in this area are discussed.

Abstract:This paper presents a representative case study of bridging UML/MARTE (unified modeling language/ modeling and analysis of real time and embedded systems) to FIACRE (intermediate format for the architectures of embedded distributed components), and discusses in detail two sub-problems of semantic mapping and syntactic transformation respectively. At the semantic level, the semantic mapping rules are developed using model transformation technology so as to implement the transformation between metamodels. At the syntactic level, the concrete syntax rules are built on the metamodels so that textual programs could be generated. Based on the case study, the general framework and corresponding key techniques are discussed. In addition, both the advantages and deficiencies of the work are concluded.

Abstract:This paper introduces an ontology-aided schema matching method in the mapping-based data exchange framework. The decision tree learning and WordNet are used to match attribute names. A data type ontology is constructed to compute semantic distance between attribute data types. Also, domain ontologies can be used to detect 1:n semantic matches. The three steps improve the match quality steadily. Experiments of several real applications show encouraging results, yielding high precision and recall measures.

Abstract:In order to deal with the memory bottleneck in high level synthesis tools for sliding-window operation, this paper presents a parameterized memory architecture for high level synthesis to automatically generate the hardware frames for all window processing applications. A three-level memory structure is designed to use inner-loop and outer-loop data completely, and at the same time shifted registers are used to make hardware design simpler. Compared with the related works, this approach can achieve a speedup of 2.13 to 3.8 times, and enhance the execution frequency from 69MHZ to 238.7MHZ.

Abstract:A number of package cohesion metrics have been proposed in the last decade, but they mainly converge on intra-package data dependencies between classes, which are inadequate to represent the semantics of packages in many cases. To address this problem, the authors first classify packages into four categories in terms of the kinds of their tasks. Next, a new package cohesion called CRC based on client usages is proposed by considering the fact that several classes are closely related if they are always reused together. And then the application areas of CRC in terms of the package classification framework are analyzed. Finally, a CRC measure called HC is presented. Compared to existing package cohesion metrics, HC considers not only intra-package but also inter-package data dependencies. It is hence able to reveal semantic relationships between classes. Furthermore, HC takes into account how the clients of a package use the package, thereby providing a finer-grain evaluation of the cohesion of a package. Experimental results demonstrates the effectiveness of HC, which likewise proves the feasibility of CRC.

Abstract:Evolutionary multi-objective optimization (EMO), whose main task is to deal with multi-objective optimization problems by evolutionary computation, has become a hot topic in evolutionary computation community. After summarizing the EMO algorithms before 2003 briefly, the recent advances in EMO are discussed in details. The current research directions are concluded. On the one hand, more new evolutionary paradigms have been introduced into EMO community, such as particle swarm optimization, artificial immune systems, and estimation distribution algorithms. On the other hand, in order to deal with many-objective optimization problems, many new dominance schemes different from traditional Pareto-dominance come forth. Furthermore, the essential characteristics of multi-objective optimization problems are deeply investigated. This paper also gives experimental comparison of several representative algorithms. Finally, several viewpoints for the future research of EMO are proposed.

Abstract:How to decrease the observation variables for strong planning under partial observation is explored. Beginning from a domain under no observation, add necessary observation variables gradually to get a minimal set of observation variables necessary. Two methods are presented to decrease observation variables. With the former, when any of the two distinct states of the domain can be distinguished by an observation variable, this algorithm can find a minimal set of observation variables necessary for the execution of a plan. With the latter, when there are states that can’t be distinguished by only one observation variable, this algorithm can find a set of observation variables as small as possible which are necessary for the execution of a plan.

Abstract:The simulated binary crossover (SBX) has been extensively adopted in the real-coded multiobjective evolutionary algorithms (MOEAs). Through the comparisons and analyses of the SBX and the mutation operator in the evolution strategy (ES), this paper proposes a normal distribution crossover (NDX) with the introduction of discrete recombination operator in ES. The NDX and SBX operators are compared and analyzed through an example designed in the one dimensional search space, and then the NDX is applied to a steady-state multiobjective evolutionary algorithm named ε-MOEA (ε-dominance based multiobjective evolutionary algorithm) proposed by Deb, et al. The algorithmε-MOEA with NDX (ε-MOEA/NDX) has been tested and compared on the 10 benchmark functions taken from the ZDT and DTLZ standard test suites. Experimental results demonstrate that algorithmε-MOEA/NDX is distinctly superior to theε-MOEA/SBX and NSGA-II algorithms, which are representatives of the state-of-the-art in the area.

Abstract:Based on the study of T-coloring problem, multiagent systems and evolutionary algorithms are integrated to form a new algorithm, multiagent evolutionary algorithm for T-coloring problem (MAEA-TCP). Then, this method is used to deal with the realistic frequency assignment problem, and has achieved encouraging results. In this algorithm, each agent is fixed on a lattice point of agent lattice as a possible solution. In order to increase energies, they compete or cooperate with their neighbors. They can also use knowledge to achieve their aims. Three evolutionary operators are designed for simulating the intelligent behaviors of agent, such as competition, self-learning and so on. The evolutionary operators are controlled through evolution, so that the populations can evolve. Experiments on large random graph instances and Philadelphia instances show that MAEA-TCP is a more encouraging algorithm than other methods.

Abstract:To make up the limitations of existing schema matching methods based on schema structure information, a schema matching model called SKM (schema and reused knowledge based matching model) is proposed based on schema structure information and known matching knowledge. In this model, neural network influence procedure is imitated to realize semantic matching reasoning. The known matching knowledge is reused to mine the deep semantic relation between two schemas. It is also reused to curtail uncertain threshold interval automatically to specify the threshold for decreasing manual intervention. A simple approach of specifying matching relation between two matching elements is given. In the meantime, a self-learning adaptive and iterative model is presented to mine and enrich the known matching knowledge. Experimental results show that the SKM is feasible.

Abstract:Regarding to the characteristic of Gbest model and Lbest model in original particle swarm optimization, a neighborhood topology structure is developed, called multi-cluster structure. Moreover, a varying neighborhood strategy based on multi-cluster is proposed to coordinate exploration and exploitation. Furthermore, the information dissemination of several topologies is analyzed theoretically, and the statistical properties of canonical topologies and varying neighborhood topology are analyzed from graph theory. Gaussian dynamic particle swarm with several canonical topologies and varying topology are tested on five benchmark functions which are commonly used in the evolutionary computation. Experimental simulation results demonstrate that dynamic probabilistic particle swarm optimization with the varying neighborhood topology can solve complex optimization problems and escape from local optimal solutions efficiently. The results also reveal that the proposed method enhances the global search ability obviously.

Abstract:This paper makes a comprehensive survey of the recommender system research aiming to facilitate readers to understand this field. First the research background is introduced, including commercial application demands, academic institutes, conferences and journals. After formally and informally describing the recommendation problem, a comparison study is conducted based on categorized algorithms. In addition, the commonly adopted benchmarked datasets and evaluation methods are exhibited and most difficulties and future directions are concluded.

Abstract:In this paper, current research issues and the problems of Internet naming are discussed. The existing namespace and key techniques in this field are categorized and introduced. At the end of the paper, the key ideas in research of naming and the possible research trends in the future are discussed.

Abstract:In this paper, the lifetime of wireless sensor networks (WSNs) is modeled as a function of μ and , i.e. LT=f(μ,?), where ? is the mean value of energy dissipation when transmit one unit data to a base station or sink, and ? denotes the flow distribution in a 2D WSN area. The lifetime analysis for three famous routing protocols is presented in detail based on the model mentioned above. With the methods proposed in this paper, the average energy dissipation rate of anywhere and anytime in WSNs can be calculated. The metrics presented in this paper has been validated by simulation results.

Abstract:An application layer multicast mechanism, CD-Media, is proposed based on the combination of central-control and distributed self-organization. This mechanism with different hierarchies is stable and suitable for the quasi-real-time application. Special servers with high performance is deployed in the higher levels to organize the star topology, and they are responsible for the construction and maintenance of Mesh network and multicast tree in the lower levels. In the lower levels a distributed protocol for self-organization is used and Mesh-first strategy is adopted in the Cluster. Multicast technologies both in application layer and network layer are combined to make use of their own advantages to achieve higher performance. An experiment is delicately designed to show the advantage of CD-Media, and it is convinced that it will be a promising mechanism in overly multicast.

Abstract:The composition of access control policies is the key to determine access control policies for distributed aggregated resource. To regulate policy composition and guarantee its correctness, an algebraic model called APoCA (attribute-based access control policy composition algebra) is proposed for composing access control policy. In APoCA, an authorization relation between entities is described at the attribute level. APoCA fertilizes the existing formal frameworks by taking into account the computation of attribute values. Several examples are given to demonstrate the expressiveness of ApoCA. ApoCA can be used for more complex applications. In addition, access control policies of aggregated resources can be formulated as expressions of the algebra. Several algebraic properties of policy expressions are discussed. It shows that the algebraic properties of policy expressions can be used to verify whether policy composition results meet the protection needs of each party. Furthermore, a translator is devised to convert the policy expressions into logic programs, which provides the basis for the evaluation and application of access control policies for aggregated resources.

Abstract:Two methods are presented to calculate the lower bound and upper bound on the bisection width of H-Torus topology. These two methods can also be applied to the 2D Torus topology. A method is presented to calculate the exact bisection width for H-Torus too. But this method has unacceptable complexity and can only be accepted with small scale. It is shown that H-Torus topology has larger bisection width. Regarding precision, the lower bound and upper bound introduced in this paper are greatly improved. This result strongly supports the design of scalable routers.

Abstract:A graph model of the resource reuse problem for relay networks is constructed. Based on this model, an innovative approach called ARRS (adaptive resource reuse scheduling) is presented to enhance the resource utilization. Since the key process of ARRS involves in graph coloring, which is NP-hard, an approximation algorithm called ARRS_Greedy is provided for optimal resource reuse constrained coloring of vertex weighted graph G(V,E,W). ARRS_Greedy is proved to obtain a tight approximation ratio of ?(Δ+1)/2? in time O(|V|²), where Δ is the maximum degree of vertex in graph G. Simulations demonstrate that ARRS_Greedy achieves near optimal performance in practice and prove that ARRS is dynamically adaptive to network status and thus enhances the system capacity more efficiently than previous solutions.

Abstract:To improve the quality of the reconstructed image in any tamper condition, this work proposes a self-embedding watermarking scheme with robustness against watermark alterations, and discusses the reasonability of the predefined threshold and the reliability of tamper detection. The proposed scheme firstly sets the least significant bit (LSB) of three-quarter pixels and two LSBs of the residual pixels in the original image to zero. And then the low-frequency feature image is obtained by quantizing the low-frequency wavelet coefficients of the original image content. The improved security watermark, which is the binary code of the scramble version of the low-frequency feature image, is embedded into the LSBs which were set to zero. While the image authentication, the proposed method is able to discriminate the malicious modifications from the mild distortions according to the predefined threshold to enhance the robustness against innocuous alterations such as watermark changes and channel noise. Theoretical analysis and simulation results show that the proposed scheme can discriminate the different modifications according to the predefined threshold no matter the embedded watermark in the host image is randomly or regionally tampered. The quality of the recovery image can be effectively improved due to the fact that the different reconstructed methods are adopted for the different tamper blocks.

Abstract:A security-state-region-based (SSR-based) model called security-state-region-based evaluation model (SSREM) is proposed, which integrates the assessment based on the attack graph and the evaluation according to criteria together. In the model, the attack result is divided into the change in the attack ability and environment. The cause and effect relationship among them lays a foundation for building mathematic equations. After that, the definition of SSR is proposed, and also curve and surface fitting recurring to Matlab is used to analyze the attack trend, the result of which provides a theoretical basis for the division of SSR and the network security assessment based on SSR. Experiments in the posterior part of the paper show that, the evaluation according to SSREM can reflect how difficult it is to enter into different states through SSR and the tendency coefficient of security state region (TC_SSR), which can be used for reference by quantitative evaluation of network security.

Abstract:Some improvements on three aspects have been made for the self-healing key distribution scheme proposed by Staddon et al. First, an efficient long-lived scheme which is unconditional secure instead of computational secure is proposed to lower the cost of computation and communication. Second, the capability of session key recovery of members is strengthened, which enables the members to recover some reasonable session keys in a certain special situation. Third, the number of broadcast messages and that of personal keys stored in users’ memory are reduced.

Abstract:Based on the previous work on automatic detection of shared fragments, this paper proposes a fragment-based delta encoding approach denoted FDE. A feature of FDE is that it can reuse similar content at fragment granularity, and can be deployed transparently to the existing WWW infrastructure. Experiments on 16 popular Web sites show that FDE can provide more bandwidth savings and latency reduction than existing solutions.