scholarly journals QoS Based Discovery and Service Provider System

2019 ◽  
pp. 197-204
Author(s):  
Ramesh Kumar ◽  
Lavanya V ◽  
Karthika R ◽  
Harshini B
Keyword(s):  
Web Services ◽  
A Priori ◽  
Search Space ◽  
Added Value ◽  
Layer By Layer ◽  
Semantic Matching ◽  
Semantic Approach ◽  
Service Patterns ◽  
Numeric Estimation ◽  
Multiple Services

We propose a two-step, context-based semantic approach to the problem of matching and ranking Web services for possible service composition. Semantic understanding of Web services may provide added value by identifying new possibilities for compositions of services and context-based semantic. The semantic matching ranking approach is unique since it provides the Web service designer with an explicit numeric estimation of the extent to which a possible composition. This process consists of multiple services that can be executed in sequence or in a parallel process. Given a service request, a set of candidates (available services and service patterns) is dynamically generated layer by layer from inputs to outputs of this request. For each layer, the algorithm traverses a priori search space which is a set of service patterns from historical solutions, then it searches available services from the repositories. That means each layer contains all services and service patterns that can be executed with a set of outputs provided by previous layers. The search process terminates until all the outputs of a request are obtained.

A Multi-Level Framework for Validation of Ontology-Driven and Community-Based Web Services Composition

2012 ◽  
Vol 3 (1) ◽  
pp. 58-72
Author(s):  
Nacéra Bennacer ◽  
Guy Vidal-Naquet
Keyword(s):  
Web Services ◽  
Description Logic ◽  
A Priori ◽  
Search Space ◽  
Community Based ◽  
Execution Plan ◽  
Multi Level ◽  
Priori Information ◽  
Dynamic Execution ◽  
Execution Order

This paper proposes an Ontology-driven and Community-based Web Services (OCWS) framework which aims at automating discovery, composition and execution of web services. The purpose is to validate and to execute a user’s request built from the composition of a set of OCWS descriptions and a set of user constraints. The defined framework separates clearly the OCWS external descriptions from internal realistic implementations of e-services. It identifies three levels: the knowledge level, the community level and e-services level and uses different participant agents deployed in a distributed architecture. First, the reasoner agent uses a description logic extended for actions in order to reason about: (i) consistency of the pre-conditions and post-conditions of OCWS descriptions and the user constraints with ontologies semantics, (ii) consistency of the workflow matching assertions and the execution dependency graph. Then the execution plan model is generated automatically to be run by the composer agents using the dynamic execution plan algorithm (DEPA), according to the workflow matching and the established execution order. The community composer agents invoke the appropriate e-services and ensure that the non functional constraints are satisfied. DEPA algorithm works dynamically without a priori information about e-services states and has interesting properties such as taking into account the non-determinism of e-services and reducing the search space.

Enriching Textual Search Results at Query Time Using Entity Mining, Linked Data and Link Analysis

2014 ◽  
Vol 08 (04) ◽  
pp. 515-544 ◽  
Author(s):  
Pavlos Fafalios ◽  
Panagiotis Papadakos ◽  
Yannis Tzitzikas
Keyword(s):  
Semantic Information ◽  
A Priori ◽  
Open Data ◽  
Search Space ◽  
Link Analysis ◽  
Query Time ◽  
Search Results ◽  
Ranking Scheme ◽  
Web Of Data ◽  
Comparative Results

The integration of the classical Web (of documents) with the emerging Web of Data is a challenging vision. In this paper we focus on an integration approach during searching which aims at enriching the responses of non-semantic search systems with semantic information, i.e. Linked Open Data (LOD), and exploiting the outcome for offering advanced exploratory search services which provide an overview of the search space and allow the users to explore the related LOD. We use named entities identified in the search results for automatically connecting search hits with LOD and we consider a scenario where this entity-based integration is performed at query time with no human effort and no a-priori indexing which is beneficial in terms of configurability and freshness. However, the number of identified entities can be high and the same is true for the semantic information about these entities that can be fetched from the available LOD. To this end, in this paper we propose a Link Analysis-based method which is used for ranking (and thus selecting to show) the more important semantic information related to the search results. We report the results of a survey regarding the marine domain with promising results, and comparative results that illustrate the effectiveness of the proposed (PageRank-based) ranking scheme. Finally, we report experimental results regarding efficiency showing that the proposed functionality can be offered even at query time.

A Two Phases Self-healing Framework for Service-oriented Systems

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Amal Alhosban ◽  
Zaki Malik ◽  
Khayyam Hashmi ◽  
Brahim Medjahed ◽  
Hassan Al-Ababneh
Keyword(s):  
Web Services ◽  
A Priori ◽  
Fault Management ◽  
Service Selection ◽  
Exception Handling ◽  
Self Healing ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Improved Performance ◽  
High Level

Service-Oriented Architectures (SOA) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently a priori unknown, how to deliver reliable Web services compositions is a significant and challenging problem. Services involved in an SOA often do not operate under a single processing environment and need to communicate using different protocols over a network. Under such conditions, designing a fault management system that is both efficient and extensible is a challenging task. In this article, we propose SFSS, a self-healing framework for SOA fault management. SFSS is predicting, identifying, and solving faults in SOAs. In SFSS, we identified a set of high-level exception handling strategies based on the QoS performances of different component services and the preferences articled by the service consumers. Multiple recovery plans are generated and evaluated according to the performance of the selected component services, and then we execute the best recovery plan. We assess the overall user dependence (i.e., the service is independent of other services) using the generated plan and the available invocation information of the component services. Due to the experiment results, the given technique enhances the service selection quality by choosing the services that have the highest score and betters the overall system performance. The experiment results indicate the applicability of SFSS and show improved performance in comparison to similar approaches.

scholarly journals The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

2014 ◽  
Vol 7 (2) ◽  
pp. 1645-1689
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Statistical Tests ◽  
Surface Ozone ◽  
A Priori ◽  
Thermal Infrared ◽  
Added Value ◽  
Chemical Transport Model ◽  
Geo Satellite ◽  
Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

scholarly journals An iterative and automated computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic samples

2019 ◽  
Author(s):  
Mathias Kuhring ◽  
Joerg Doellinger ◽  
Andreas Nitsche ◽  
Thilo Muth ◽  
Bernhard Y. Renard
Keyword(s):  
Statistical Power ◽  
Sequence Data ◽  
A Priori ◽  
Search Space ◽  
Strain Level ◽  
Reference Sequence ◽  
Viral Origin ◽  
Identification Of Species ◽  
Taxonomic Assignments

AbstractUntargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes.We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to improve candidate confidence.We apply our iterative workflow on several samples of bacterial and viral origin. In comparison to non-iterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted and continuously growing sequence resources such as the NCBI databases and is available under open-source license at https://gitlab.com/rki_bioinformatics.

scholarly journals RECPARSER: A Recursive Semantic Parsing Framework for Text-to-SQL Task

2020 ◽  
Author(s):  
Yu Zeng ◽  
Yan Gao ◽  
Jiaqi Guo ◽  
Bei Chen ◽  
Qian Liu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Search Space ◽  
Layer By Layer ◽  
Semantic Parsing ◽  
Query Generation ◽  
Sql Query ◽  
Generation Problem

Neural semantic parsers usually fail to parse long and complicated utterances into nested SQL queries, due to the large search space. In this paper, we propose a novel recursive semantic parsing framework called RECPARSER to generate the nested SQL query layer-by-layer. It decomposes the complicated nested SQL query generation problem into several progressive non-nested SQL query generation problems. Furthermore, we propose a novel Question Decomposer module to explicitly encourage RECPARSER to focus on different components of an utterance when predicting SQL queries of different layers. Experiments on the Spider dataset show that our approach is more effective compared to the previous works at predicting the nested SQL queries. In addition, we achieve an overall accuracy that is comparable with state-of-the-art approaches.

Discovering Homogenous Service Framework Based on Matching Mechanism and Clustering

2011 ◽  
Vol 341-342 ◽  
pp. 462-466
Author(s):  
Meng Wang ◽  
Shu Yu Li
Keyword(s):  
Web Services ◽  
Web Service ◽  
Search Engine ◽  
Search Space ◽  
Research Direction ◽  
The Internet ◽  
Ongoing Research ◽  
Service Community ◽  
Matching Mechanism ◽  
Service Framework

How to efficiently select Web services that can best meet the requirements of consumers is an ongoing research direction in Web service community. However, current discovery systems support either WSDL or OWL-S Web services but not both.Through the automatically collected WSDL files and the OWL-S web service related matching mechanism, the idea of transforming various existing web services on the Internet into a service cluster of similar homogeneous , then we can create a service search engine successfully and at the same time the search space can be reduced. By means of providing a mechanism for matching the characteristics properties of relevant web services, we can put them all together into a group which can be found and applied.

Joint DNA-based Disaster Victim Identification

2021 ◽  
Author(s):  
Magnus Dehli Vigeland ◽  
Thore Egeland
Keyword(s):  
A Priori ◽  
Search Space ◽  
R Package ◽  
Individual Identification ◽  
Disaster Victim Identification ◽  
Data Set ◽  
Victim Identification ◽  
Joint Identification ◽  
Available Information ◽  
User Friendly

Abstract We address computational and statistical aspects of DNA-based identification of victims in the aftermath of disasters. Current methods and software for such identification typically consider each victim individually, leading to suboptimal power of identification and potential inconsistencies in the statistical summary of the evidence. We resolve these problems by performing joint identification of all victims, using the complete genetic data set. Individual identification probabilities, conditional on all available information, are derived from the joint solution in the form of posterior pairing probabilities. A closed formula is obtained for the a priori number of possible joint solutions to a given DVI problem. This number increases quickly with the number of victims and missing persons, posing computational challenges for brute force approaches. We address this complexity with a preparatory sequential step aiming to reduce the search space. The examples show that realistic cases are handled efficiently. User-friendly implementations of all methods are provided in the R package dvir, freely available on all platforms.

An extended artificial bee colony with local search for solving the Skyline-based web services composition under interval QoS properties

2021 ◽  
pp. 1-16
Author(s):  
Ghizlane Khababa ◽  
Fateh Seghir ◽  
Sadik Bessou
Keyword(s):  
Web Services ◽  
Local Search ◽  
Artificial Bee Colony ◽  
Search Space ◽  
Evolutionary Strategy ◽  
Extended Version ◽  
The Public ◽  
Bee Colony ◽  
Skyline Operator ◽  
Experimental Comparisons

 In this paper, we introduce an extended version of artificial bee colony with a local search method (EABC) for solving the QoS uncertainty-aware web service composition (IQSC) problem, where the ambiguity of the QoS properties are represented using the interval-number model. At first, we formulate the addressed problem as an interval constrained single-objective optimization model. Then, we use the skyline operator to prune the redundant and dominated web services from their sets of functionally equivalent ones. Whereas, EABC is employed to solve the IQSC problem in a reduced search space more effectively and more efficiently. For the purpose of validation of the performance and the efficiency of the proposed approach, we present the experimental comparisons to an existing skyline-based PSO, an efficient discrete gbest-guided artificial bee colony and a recently provided Harris Hawks optimization with an elite evolutionary strategy algorithms on an interval extended version of the public QWS dataset.

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