18193677
Preserving and Exploiting Genetic Diversity in Evolutionary Programming Algorithms
Evolution programming (EP) is an important category of evolutionary algorithms. It relies primarily on mutation operators to search for solutions of function optimization problems (FOPs). Recently a series of new mutation operators have been proposed in order to improve the performance of EP. One prominent example is the fast EP (FEP) algorithm which employs a mutation operator based on the Cauchy distribution instead of the commonly used Gaussian distribution. In this paper, we seek to improve the performance of EP via exploring another important factor of EP, namely, the selection strategy. Three selection rules R1-R3 have been presented to encourage both fitness diversity and solution diversity. Meanwhile, two solution exchange rules R4 and R5 have been introduced to further exploit the preserved genetic diversity. Simple theoretical analysis suggests that through the proper use of R1-R5, EP is more likely to find high-fitness solutions quickly. Our claim has been examined on 25 benchmark functions. Empirical evidence shows that our solution selection and exchange rules can significantly enhance the performance of EP.
8202363
Coordinated Services Provision in Peer-to-Peer Environments
In recent years, inspired by the emerging Web services standard and peer-to-peer technology, a new federated service providing (FSP) system paradigm has attracted increasing research interests. Many existing systems have either explicitly or implicitly followed this paradigm. Instead of exchanging files, peers in FSP systems share their computation resources in order to offer domain-specific services. In this paper, we focused on the coordination problem of how to self-organize the service group structures in response to the varying service demand. We presented our solution in the form of a coordination mechanism, which includes a labor-market model, a recruiting protocol, and a policy-driven decision architecture. Peers make their service providing decisions based on their local policies, which can be added, removed, or modified by users. A general methodology is introduced in this paper to facilitate policy design. Specifically, a heuristic inspired by the extremal optimization technique is utilized to handle potential inconsistencies among policies. A stimulus-response mechanism was further applied to make the decision process adjustable. Experiments under five application scenarios verified our ideas and demonstrated the effectiveness of our coordination mechanism.
15177546
Semantic enhanced rule driven workflow execution in Collaborative Virtual Enterprise
Globalization leads to an efficient new business paradigm generally known as collaborative virtual enterprise (CVE) which demands flexible service orchestration and robust workflow execution. As two major service orchestration strategies, OWL-S and BPEL have their own strength and deficiencies. To meet the challenge in CVE, in this paper, we propose a workflow execution system (WES) that takes advantage of the complementary strengths of these two technologies. On the one hand, having semantic support, OWL-S is used in dynamic service discovery and composition at high level. On the other hand, at the concrete level, industry-based BPEL is exploited in service execution. The description of each semantic Web service is enhanced with rule-based modeling of the essential business logic behind the service interface. In order to realize interoperability in OWL-S and BPEL without loss of semantic information, we further proposed an OWLS2BPEL Mapper to facilitate the workflow robustness and support rule evaluation to increase responsiveness to customers. A concrete scenario in PC manufacturing collaborative virtual enterprise is analyzed to demonstrate the effectiveness of our workflow execution system.
537363
Change propagation algorithm in a unified feature modeling scheme
Product lifecycle stages are inter-related and mutually constraining. Due to the sequential nature of the product development processes, some constraints or conflicts may emerge in a later stage and require modifications to the decisions made in earlier stages. The iterations between stages are hence unavoidable and must be managed carefully to maintain the consistency, integrity and validity of product information models. Due to the inter- or intra-stage relations, a chain of changes is very likely to occur as the consequence of an initial change. Modeling and maintaining these relations are important in collaborative engineering to evolve the state of the whole product model in a consistent manner. This paper introduces a new method of modeling associative engineering relations in a unified feature modeling scheme and elaborates a change propagation algorithm for the information consistency control among multiple applications of product lifecycle stages. The algorithm is established on a JTMS-based dependency network. Two case studies are used to illustrate the proposed dependency network and change propagation algorithm.
14272859
Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown
The ant colony optimization (ACO) algorithm is a metaheuristic inspired from the behavior of foraging ants. Instead of exploring its ability in finding optimal solutions, the current study investigates another unique property - self-healing mechanism for resource allocation in a service-oriented environment where unexpected resource breakdown can occur. A system architecture is first proposed to detect, diagnose and react to disturbances. Then the performance of the ACO self-healing mechanism is tested and compared based on a modified benchmark problem. The experimental results show that the self-healing mechanism can promptly recover an obsolete schedule with high quality solutions.
8577812
Dynamic Self-Healing for Service Flows with Semantic Web Services
With an increasing complexity of business processes, self-healing capability is becoming an important issue in order to support robust service flow execution. In this paper, a dynamic self-healing mechanism is proposed, which can dynamically identify suitable alternatives and replace faulty services such that a service flow can be performed successfully despite of unexpected exceptions. This mechanism explicitly utilizes semantic Web services for service matching and selection of a composite service in business service flow, and Semantic Web services are equipped with rich business rules in a domain-dependent manner. We explore the self-healing mechanism for supporting self-healable service flow execution which is modeled in BPEL4WS. A demo system of self-healing capable service flow execution is built to validate its effectiveness by a concrete scenario, PC manufacturing application.
25276326
Web-Based Service Management of Distributed Learning
This paper tries to design structure of Web-Based Service Management of Distributed Learning (WSMDL). The structure integrating IT service and Educational Auxiliary System service flow. Help desk becomes only interface for all levels of users according to their individual demands. Though analysis of service events and user’s feedback in service flow, it also provides the decision-making to improve the quality of Web-based Service Management of Distributed Learning Service Management. The paper also depicts the functions of WSMDL.
7987221
Using VRML and JAVA to Build Virtual Game-Based Learning Environment for Addition and Subtraction Operation
How to make elementary mathematics education vivid and interesting? In this paper, we describe how to use VRML and JAVA to build a virtual game-based learning environment (VGBLE), in which children can learn addition and subtraction operation through games and hence children’s interesting in learning and effects will be improved.
472296
A Fast Center of Mass Estimation Algorithm for Coordinates of IR Markers
For the binocular vision system based on light-weighted passive IR reflective markers and IR LED array PCB board, which is used to measure the 3-D motion parameters of rocket motor, the most important issue is determining the coordinates of infrared markers. In order to solve this problem, a fast center of mass estimation algorithm was proposed in this paper. The new algorithm segments the infrared image by self-adapting thresholding method firstly, and then calculating the center of mass of infrared markers by improved statistical averaging technique. A comparison was made between the newly developed algorithm and other algorithms such as traditional statistical averaging, FFT and least-squares method. The result indicates that the new algorithm is more suited for high-speed motion analysis because of high accuracy and faster processing speed. Tests performed on real-world images show that the algorithm can greatly improve the speed of the calculation and ensure the demand of precision on the basis of the better image segmentation result and improved statistical averaging technique.
16001718
Fine-Grained Progressive Algorithm Based on HMJ
Wide-area distribution raises significant performance problems for traditional query processing techniques as data access becomes less predictable due to link congestion, load imbalances, and temporary outages. Non-blocking joining query execution is a promising approach to coping with unpredictability in such environments because of reactively scheduling background processing. Classical non-blocking two-way joining technique based on hash-merge (HMJ), however, fail to deliver acceptable performance in such a scenario where relatively short intermittent delay exists in the gross. We have developed a fairly fine-grained hash-merge join, called HMJ-FG, which has employed a replacement selection tree, allowing many disparted segments to be active in parallel. Using the optimization implementation along with simulation obtained by Tao, we show that HMJ-FG is an effective solution for providing fast query responses to users even in the presence of the longer-term of data sources appeared as unavailability. Theory and experimental results show that our technique delivers results significantly fast under unreliable network.
15133148
Modeling Image Data for Effective Indexing and Retrieval in Large General Image Databases
In this paper, we propose an image semantic model based on the knowledge and criteria in the field of linguistics and taxonomy. Our work bridges the "semantic gap" by seamlessly exploiting the synergy of both visual feature processing and semantic relevance computation in a new way, and provides improved query efficiency and effectiveness for large general image databases. Our main contributions are as follows: we design novel data structures, namely, a lexical hierarchy, an image-semantic hierarchy, and a number of atomic semantic domains, to capture the semantics and the features of the database, and to provide the indexing scheme. We present a novel image query algorithm based on the proposed structures. In addition, we propose a novel term expansion mechanism to improve the lexical processing. Our extensive experiments indicate that our proposed techniques are effective in achieving high runtime performance with improved retrieval accuracy. The experiments also show that the proposed method has good scalability.