265743
SOA Collaboration Modeling, Analysis, and Simulation in PSML-C
This paper extends the ebXML Web services development framework to introduce a new collaboration framework, which is based on the collaboration specification language PSML-C (Process Specification and Modeling Language for Collaboration), CCSOA (Consumer-Centric Service-Oriented Architecture), and DDSOS (Dynamic Distributed Service-Oriented Simulation) framework. Since collaborations are inevitable and play a critical role in SOA, an effective framework will greatly reduce the effort for rapid and adaptive service composition, simulation, evaluation, and collaboration. The PSML-C collaboration framework provides a service-oriented infrastructure for process collaboration specification, modeling, design, code generation, simulation, deployment, execution, and management. This paper presents the concepts, architecture, enabling techniques, and illustrative examples that demonstrate the concepts and the techniques
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.
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.
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.
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.
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
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.
7693083
Pores and Ridges: Fingerprint Matching Using Level 3 Features
Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and ridge shape). Although high resolution sensors (~1000 dpi) have become commercially available and have made it possible to reliably extract Level 3 features, most automated fingerprint identification systems (AFIS) employ only Level 1 and Level 2 features. As a result, increasing the scan resolution does not provide any matching performance improvement (1998). We develop a matcher that utilizes Level 3 features, including pores and ridge contours, for 1000 dpi fingerprint matching. Level 3 features are automatically extracted using wavelet transform and Gabor filters and are locally matched using the ICP algorithm. Our experiments on a median-sized database show that Level 3 features carry significant discriminatory information. EER values are reduced (relatively ~20%) when Level 3 features are employed in combination with Level 1 and 2 features
6316461
Partitioned optimization algorithms for multiple sequence alignment
Multiple sequence alignment is an important and difficult problem in molecular biology and bioinformatics. In this paper, we propose a partitioning approach that significantly improves the solution time and quality by utilizing the locality structure of the problem. The algorithm solves the multiple sequence alignment in three stages. First, an automated and suboptimal partitioning strategy is used to divide the set of sequences into several subsections. Then a multiple sequence alignment algorithm based on ant colony optimization is used to align the sequences of each subsection. Finally, the alignment of original sequences can be obtained by assembling the result of each subsection. The ant colony algorithm is highly optimized in order to avoid local optimal traps and converge to global optimal efficiently. Experimental results show that the algorithm can significantly reduce the running time and improve the solution quality on large-scale multiple sequence alignment benchmarks.
10370670
Top-Down Design of Bulk-Synchronous Parallel Programs
This paper studies top-down program development techniques for Bulk-Synchronous Parallelism. In that context a specification formalism LOGS, for 'the Logic of Global Synchrony', has been proposed for the specification and high-level development of BSP designs. This paper extends the use of LOGS to provide support for the protection of local variables in BSP programs, thus completing the link between specifications and programs.
8180421
Better proposal distributions: object tracking using unscented particle filter
Tracking objects involves the modeling of non-linear non-Gaussian systems. On one hand, variants of Kalman filters are limited by their Gaussian assumptions. On the other hand, conventional particle filter, e.g., CONDENSATION, uses transition prior as the proposal distribution. The transition prior does not take into account current observation data, and many particles can therefore be wasted in low likelihood area. To overcome these difficulties, unscented particle filter (UPF) has recently been proposed in the field of filtering theory. In this paper, we introduce the UPF framework into audio and visual tracking. The UPF uses the unscented Kalman filter to generate sophisticated proposal distributions that seamlessly integrate the current observation, thus greatly improving the tracking performance. To evaluate the efficacy of the UPF framework, we apply it in two real-world tracking applications. One is the audio-based speaker localization, and the other is the vision-based human tracking. The experimental results are compared against those of the widely used CONDENSATION approach and have demonstrated superior tracking performance.