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This paper provides a formalized definition of the application problem of compound condition query (CCQ) and a formal method of applying requirements elicitation based on trace information space derived from trace algebra. With the formalized process of solving the application problem of CCQ, formal requirements specification of application of CCQ is given, a formalized and automatic mapping of the results of requirements elicitation to the formal requirements specification is performed, the software system model and the application code are developed. Through a sample application of comprehensive query on housing information, the feasibility of formalized and automatic software development for the application problem of CCQ is proved. The result has important implications for the other problems regarding formalization and automatic software development.

The method of node mining in social networks is divided into heuristic method and greedy method, in which the former mainly measures the importance degree of each node in the networks according to its own attributes or networks topology. As a result, it is fast but with bad accuracy. In the latter algorithm, however, spread simulation has been conducted for each node by adopting diffusion model, and then the importance of each node is calculated through comparison of the spread size. Therefore, this kind of algorithm is inefficient and inappropriate to large-scale social networks. This paper, therefore, proposes a new node mining algorithm based on greedy subgraph, having taken into account the unsatisfactory node mining results in the heuristic method and the highly complexity in greedy algorithm. In this new algorithm, the heuristic method is used first and then the greedy method is also adopted. Then, the author compares the differences of heuristic algorithm, the greedy algorithm and the algorithm proposed in this paper on the effect of node selection, the effectiveness of algorithm, the spread range and so no. it concludes that the node mining algorithm based on greedy subgraph can guarantee good optimal solution on the basis of ensuring a better node selection effect and efficiency than the classical algorithm. Besides, the theoretical applicability and actual spread effect of the proposed algorithm has also been verified.

Influence maximization algorithms in social networks are aimed at mining the most influential TOP-K nodes in the current social network, through which we will get the fastest spreading speed of information and the widest scope of influence by putting those nodes as initial active nodes and spreading them in a specific diffusion model. Nowadays, influence maximization algorithms in large-scale social networks are required to be of low time complexity and high accuracy, which are very hard to meet at the same time. The traditional Degree Centrality algorithm, despite of its simple structure and less complexity, has less satisfactory accuracy. The Closeness Centrality algorithm and the Betweenness Centrality algorithm are comparatively highly accurate having taken global metrics into consideration. However, their time complexity is also higher. Hence, a new algorithm based on Three Degrees of Influence Rule, namely, Linear-Decrescence Degree Centrality Algorithm, is proposed in this paper in order to meet the above two requirements for influence maximization algorithms in large-scale social networks. This algorithm, as a tradeoff between the low accuracy degree algorithm and other high time complexity algorithms, can meet the requirements of high accuracy and low time complexity at the same time.

Nowadays, social network web sites are becoming increasingly popular. Accordingly, viral marketing which aimed to promote products in social network received more and more attention. The Network Diffusion model describes how information or influence is propagated in a social network. It is of great importance to the viral marketing/influence maximization problem. However, there are two challenges: first, how to build the diffusion model so as to simulate the diffusion process better, and second, how improve the efficiency of the diffusion model so that it can be applied to more scalable viral marketing problems. To tackle these two problems, we proposed a Cellular Automaton based Network Diffusion (CAND) model. We also proved that the CAND model is equivalent to the Linear Threshold (LT) model under certain conditions. Moreover, the model is realized and a speed up method is used so as to improve the efficiency of the model. Experiments show that compared with the LT model, our model is much more efficient on four real life social network datasets, indicating a better scalability for Viral Marketing.

As the online social network become increasingly popular nowadays, performing viral marketing over it has become the focus of many marketing management. How to select a fixed number of initial users from the total population with the purpose of maximizing the profits has long been open as a typical discrete approximation problem. However most of the existing solutions under the setting of online social network tried to traverse every node using network properties which is time-consuming and ineffective. This paper attacks the problem successfully by implementing intelligent algorithms such as GA, DE, PSO. Considering of the huge search space, we sharply decrease the scalability of the network through analyzing the datasets and sampling the data according to a power law property. Experiment results showed that the model we designed for solving viral marketing problem outperform other current search methods.

This paper presents a novel trust mechanism and web services, and introduces the application of Web Services, and designs for submarine power distribution system model, and discusses the core that the implement of the model controls and business processes.

Model transformation is one of the core operations in model driven architecture (MDA) and engineering (MDE), which happens among heterogeneous models in various modeling languages. Constructing rules for such model transformation is time consuming and of great challenge. A question arises that how to describe these knowledge in standardized form and reuse them to construct model transformation rules quickly and in low cost. In this paper, transformation pattern is introduced and well defined according to the design pattern in software development. It represents transformation rules in a modeling language independent form and is easy to reuse. This study proposes a model transformation framework based on pattern and a rule constructing method. Seven reusable atomic patterns are given and nine rule extracting strategies based on this are figured. Finally, this study presents an algorithm which incorporates these strategies for constructing transformation rules. Case study in transformation between two business process models in BPMN and JPDL shows the applicability of the method in real model transformation.

In order to explore the dynamic process of the trust mechanism of the Internetware entities, this paper proposes a self-organizing trust model of the Internetware by means of the replicated dynamic equation based on the Wright-Fisher process, and analyzes the evolutionary direction and the stability of the Internetware system by establishing the incentive and punitive mechanism. This kind of self-organizing trust model has the function of providing a referenced model for the optimization and stability of the Internetware system, improving the credibility of the Internetware system, and making the system run in a long and stable state.

The paper explores the methods on decision of optimal strategy for online maintenance for Internetware through static Game Theory. An Online Maintenance Game Model (OMGM) is put forward, which simulating the trend of consuming resource and involving the dependent relationship and characteristics of the procedure maintenance among fault Internetwares. In the case of single fault Internetware and double dependent fault Internetwares, we studies calculation methods for comprehensive payoff of various maintenance strategies and extends methods to adopt online maintenance strategy decision for multiple fault Internetwares, thereby, technology and theoretical support are provided to guarantee the scalability and stability of Internetware.

Internetware is endowed with more flexibility in the dynamic, open network. However, it is facing a big challenge in trust evaluation on interaction between two components. This paper proposes an effective way of trust evaluation based on the punishment mechanism and proved its function to resist malicious attack. As trust relationships can be obtained by the recommendations of other Internetwares, thus a virtual trust information network naturally formed. In this way, the trust relationship of an Internetware can be derived without direct interaction. However, the problem lies in we might get malicious information and be led to misjudgment in such a complex and changeable network. Therefore, we put forward an algorithm based on the idea of RIP routing algorithm. The algorithm is proved to be efficient and reliable through experiment.

In order to increase the efficiency of routing and querying, decrease the maintenance cost of structure P2P network, a hierarchical small-world P2P networks (HSN) with low maintenance cost is proposed in this paper, which describe the methods about how to create and maintenance a P2P network. To demonstrate the value of HSN, this paper simulates Chord and HSN with different networks size and system parameters, and the result shows that (1) the route latency of HSN is smaller than O(logN) , where is the number of nodes in the P2P networks, (2) HSN maintenance cost decreased nearly the half of the Chord.

Ontology is an explicit specification of a conceptualization on semantic and knowledge. This paper presents a formal definition on ontology and gives an example. Then, a method to measuring semantic similarity is presented. Semantic similarity is divided into concept similarity and description similarity. A calculation of semantic similarity between concepts in ontology is presented by the hierarchy of ontology concepts. To make the calculation of semantic similarity between concepts more similar to human's subjective judgment, semantic similarity is divided into concept similarity and description similarity; the final semantic similarity is produced by merging concept similarity and description similarity. Finally, the optimized parameter settings are gained through the experiment results.

This paper presents a new modeling method, called CTOPN (colored timed object-oriented Petri net), to model AUV (autonomous underwater vehicle) system. Firstly, the definition of a CTOPN is introduced, then the procedure of developing a CTOPN model for AUV system and a deadlock detection algorithm is given, at last the simulation validation is done. The CTOPN model of AUV system is proved deadlock-free and the simulation result is accordance with the actual system.

This paper presents a Hierarchical Object-Oriented Petri Net (HOOPN) modeling method based on Ontology that should not only enable sharing Petri nets models on the Semantic Web but also present a high level Petri net. Previous work on formal methods for representing Petri nets mainly focuses on modeling and analyzing aspects or formats for Petri net model interchange. However, such efforts do not provide a suitable model description for using Petri nets on the Semantic Web. This paper uses the HOOPN with the Ontology concepts as a starting point for implementing the Petri net ontology. Moreover this paper uses HOOPN as the Petri net model method. HOOPN supports a wide range of Object-Oriented features including abstract, encapsulated and modularized objects, object interaction by message passing, inheritance, and polymorphism.

Requirement is very important part of software process. In order to truly meet the requirements of customer, it is necessary to establish an appropriate requirement management process, software process reorganization is particularly important. In this paper, firstly, a description of the requirement process is presented after software requirement process was analyzed from the perspective of requirement engineering. Then, analyzing and simplifying process algebraic expression, the approach of process algebra based for the requirement process reorganization is presented proceeded. Finally, the results of shows that development time are shortened, resources are saved and development efficiency is improved.

A method based on Petri net is presented for analyzing active database rules. Cyclic rule set, inconsistent rule set and contradictory rule set can be detected automatically by using Petri nets. These rule sets can be corrected or rearranged properly by the user in order to guarantee the system's termination, consistency and correctness.