18271710
Verification Framework for Dynamic Collaborative Services in Service-Oriented Architecture
This paper introduces a dynamic verification framework for collaborative services in service-oriented architecture (SOA). Collaboration plays a critical role in SOA, an effective verification framework for collaboration will greatly reduce the effort for rapid and adaptive service composition and evaluation of applications based on collaborative services. The verification framework provides a service-oriented infrastructure for completeness and consistency analyses, model-checking, simulation, and policy enforcement of process specification based on collaborative services in SOA. The paper presents the concepts, architecture, profiling techniques and illustrative examples that demonstrate the concepts and the techniques
2511748
QPIAD: Query Processing over Incomplete Autonomous Databases
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous Web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant to a user query. Ideally we would like the mediator to retrieve such relevant uncertain answers and gauge their relevance by accessing their likelihood of being relevant answers to the query. However, the autonomous nature of the databases poses several challenges, such as the restricted access privileges, limited query patterns, and sensitivity of database and network resource consumption in the Web environment. We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges to retrieve relevant uncertain answers. Our technique involves reformulating the user query based on approximate functional dependencies (AFDs) among the database attributes and ranking these queries using value distributions learned from naive Bayes classifiers. Empirical studies demonstrate the effectiveness of our approach in retrieving relevant uncertain answers with high precision, high recall and manageable cost.
5453537
Testability of Software in Service-Oriented Architecture
Service-oriented architecture (SOA) is a system architecture in which a collection of loosely coupled services communicate with each other using standard interfaces and message-exchanging protocols. As an emerging technology in software development, the SOA presents a new paradigm, and it affects the entire software development cycle including analysis, specification, design, implementation, verification, validation, maintenance and evaluation. This paper proposes several testability evaluation criteria for SOA software, which serves as a reference for both service providers and application builders to evaluate the test support to SOA software. The proposed evaluation criteria are illustrated in a stock-trading case study
5650965
L-Tree: A Dynamic Labeling Structure for Ordered XML Data
With the ever growing use of XML as a data representation format, we see an increasing need for robust, high performance XML database systems While most of the recent work focuses on efficient XML query processing, XML databases also need to support efficient updates To speed up query processing, various labeling schemes have been proposed However, the vast majority of these schemes have poor update performance In this paper, we introduce a dynamic labeling structure for XML data: L-Tree and its order-preserving labeling scheme with O(log n) amortized update cost and O(log n) bits per label L-Tree has good performance on updates without compromising the performance of query processing We present the update algorithm for L-Tree and analyze its complexity.
3132727
Query Processing over Incomplete Autonomous Databases
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant to a user query. Ideally we would like the mediator to retrieve such possible answers and gauge their relevance by accessing their likelihood of being pertinent answers to the query. The autonomous nature of web databases poses several challenges in realizing this objective. Such challenges include the restricted access privileges imposed on the data, the limited support for query patterns, and the bounded pool of database and network resources in the web environment. We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges. Our technique involves reformulating the user query based on mined correlations among the database attributes. The reformulated queries are aimed at retrieving the relevant possible answers in addition to the certain answers. QPIAD is able to gauge the relevance of such queries allowing tradeoffs in reducing the costs of database query processing and answer transmission. To support this framework, we develop methods for mining attribute correlations (in terms of Approximate Functional Dependencies), value distributions (in the form of Naive Bayes Classifiers), and selectivity estimates. We present empirical studies to demonstrate that our approach is able to effectively retrieve relevant possible answers with high precision, high recall, and manageable cost.
37282807
Testing Web Services Using Progressive Group Testing
This paper proposes progressive group testing techniques to test large number of Web services (WS) available on Internet. At the unit testing level, the WS with the same functionality are tested in group using progressively increasing number of test cases. A small number of WS that scored best will be integrated into the real environment for operational testing. At the integration testing level, many composite services will be constructed and tested by group integration testing. The results of group testing at both unit and integration levels are verified by weighted majority voting mechanisms. The weights are based on the reliability history of the WS under test. A case study is designed and implemented, where the dependency among the test cases in WS is analyzed and used to generate progressive layers of test cases.
17642380
Evolutionary Modeling of Ordinary Differential Equations for Dynamic Systems
This paper presents a new idea of modeling one-dimensional dynamic systems by higher-order ordinary differential equation (HODE) models in stead of by the ARMA models used in the traditional time series analysis. Accordingly, based on the idea of hybrid evolutionary modeling, we modify the HEMA algorithm in (Cao et al., 1998a; Cao et al., 1998b) to approach the modeling problem of HODEs for dynamic systems. Two applications of time series are used to demonstrate its effectiveness and advantages.
669399
Camera Calibration: a USU Implementation
The task of camera calibration is to estimate the intrinsic and extrinsic parameters of a camera model. Though there are some restricted techniques to infer the 3-D information about the scene from uncalibrated cameras, effective camera calibration procedures will open up the possibility of using a wide range of existing algorithms for 3-D reconstruction and recognition. The applications of camera calibration include vision-based metrology, robust visual platooning and visual docking of mobile robots where the depth information is important.
8090728
The SAHARA Model for Service Composition across Multiple Providers
Services are capabilities that enable applications and are of crucial importance to pervasive computing in next-generation networks. Service Composition is the construction of complex services from primitive ones; thus enabling rapid and flexible creation of new services. The presence of multiple independent service providers poses new and significant challenges. Managing trust across providers and verifying the performance of the components in composition become essential issues. Adapting the composed service to network and user dynamics by choosing service providers and instances is yet another challenge. In SAHARA, we are developing a comprehensive architecture for the creation, placement, and management of services for composition across independent providers. In this paper, we present a layered reference model for composition based on a classification of different kinds of composition. We then discuss the different overarching mechanisms necessary for the successful deployment of such an architecture through a variety of case-studies involving composition.
17575068
Yoda, an adaptive soft classification model: content-based similarity queries and beyond
Abstract. Providing a customized result set based upon a user preference is the ultimate objective of many content-based image retrieval systems. There are two main challenges in meeting this objective: First, there is a gap between the physical characteristics of digital images and the semantic meaning of the images. Secondly, different people may have different perceptions on the same set of images. To address both these challenges, we propose a model, named Yoda, that conceptualizes content-based querying as the task of soft classifying images into classes. These classes can overlap, and their members are different for different users. The “soft” classification is hence performed for each and every image feature, including both physical and semantic features. Subsequently, each image will be ranked based on the weighted aggregation of its classification memberships. The weights are user-dependent, and hence different users would obtain different result sets for the same query. Yoda employs a fuzzy-logic based aggregation function for ranking images. We show that, in addition to some performance benefits, fuzzy aggregation is less sensitive to noise and can support disjunctive queries as compared to weighted-average aggregation used by other content-based image retrieval systems. Finally, since Yoda heavily relies on user-dependent weights (i.e., user profiles) for the aggregation task, we utilize the users' relevance feedback to improve the profiles using genetic algorithms (GA). Our learning mechanism requires fewer user interactions, and results in a faster convergence to the user's preferences as compared to other learning techniques.
1773435
Chava: reverse engineering and tracking of Java applets
Java applets have been used increasingly on Web sites to perform client-side processing and provide dynamic content. While many Web site analysis tools are available, their focus has been on static HTML content and most ignore applet code completely. The paper presents Chava, a system that analyzes and tracks changes in Java applets. The tool extracts information from applet code about classes, methods, fields and their relationships into a relational database. Supplementary checksum information in the database is used to detect changes in two versions of a Java applet. Given our Java data model, a suite of programs that query, visualize, and analyze the structural information were generated automatically from CIAO, a retargetable reverse engineering system. Chava is able to process either Java source files or compiled class files, making it possible to analyze remote applets, whose source code is unavailable. The information can be combined with HTML analysis tools to track both the static and dynamic content of many Web sites. The paper presents our data model for Java and describes the implementation of Chava. Advanced reverse engineering tasks such as reachability analysis, clustering, and program differencing can be built on top of Chava to support design recovery and selective regression testing. In particular, we show how Chava is used to compare several Java Development Kit (JDK) versions to help spot changes that might impact Java developers. Performance numbers indicate that the tool scales well.