Reconciling Semantic Heterogeneity in Web Services Composition

Li, Xitong; Madnick, Stuart E.; Zhu, Hongwei; Fan, Yushun

doi:10.2139/ssrn.1478025

Cited by 21 publications

(16 citation statements)

References 30 publications

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“…Besides, context conflicts cause data-level semantic heterogeneity among DP services [62], [65]. Incorporating the context information in this work for reconciling context differences is our planned future work.…”

Section: Discussionmentioning

confidence: 99%

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Zhou

Sellami

Gaaloul

et al. 2013

IEEE Trans. Automat. Sci. Eng.

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In service-oriented computing, a user usually needs to locate a desired service for: (i) fulfilling her requirements or (ii) replacing a service, which disappears or is unavailable for some reasons, to perform an interaction. With the increasing number of services available within an enterprise and over the Internet, locating a service online may not be appropriate from the performance perspective, especially in large Internet-based service repositories. Instead, services usually need to be clustered according to their similarity. Thereafter, services in one or several clusters are necessary to be examined online during dynamic service discovery. In this paper, we propose to cluster data providing (DP) services using a refined fuzzy -means algorithm. We consider the composite relation between DP service elements (i.e., input, output, and semantic relation between them) when representing DP services in terms of vectors. A DP service vector is assigned to one or multiple clusters with certain degrees. In addition, we introduce some operations for managing service clusters, when new services emerge or existing services disappear or become unavailable. When grouping similar services into one cluster, while partitioning different services into different clusters, the capability of service search engine is improved significantly. We have prototyped our approach and the source code is freely available on the web. We have evaluated our clustering approach in different settings and the results are very promising.Note to Practitioners-DP services are common nowadays, and there are a huge number of DP services in the Internet-scale environment. Locating an appropriate DP service accurately and efficiently with respect to the requirements of a certain requestor is a challenging task. This work presents a novel clustering-oriented approach, which aims to group DP services into clusters offline leveraging the semantic description of these DP services, and provides operations for managing these clusters. The clustering procedure is conducted by means of a machine learning technique which is a refined fuzzy -means method. A DP service can be assigned to one or several clusters with certain degrees. DP service clusters constitute a cluster network. Operations are provided for facilitating the evolution of cluster network, when a DP service emerges or disappears sometime for some reason. A prototype has been implemented and the approach has been evaluated on two test collections of DP services considering factors impacting the efficiency. Our method can be readily used in industrial DP service repository for supporting DP service discovery and replacement.

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Section: Discussionmentioning

confidence: 99%

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Zhou

Sellami

Gaaloul

et al. 2013

IEEE Trans. Automat. Sci. Eng.

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“…Klímek and Necaský [8] introduced a model-driven method to automatically generate XSLT for lifting and lowering schema mappings and its prototype implementation. Li et al [9] presented an approach to reconciliate semantic conflicts in the composition of web services. They used COIN ontology, SAWSDL and mapping algorithms to handle complex differences by using minimal numbers of predefined transformations.…”

Section: Related Workmentioning

confidence: 99%

Service-Level Interoperability Issues of Platform as a Service

Andročec

Vrček

Küngas

2015

2015 IEEE World Congress on Services

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The numerous heterogeneities among different providers make platform as a service interoperability an interesting and complex research and practical problem. For example, each provider offers its own remote application programming interfaces (APIs). The main aim of this paper is to identify and address service-level interoperability issues when using APIs from different commercial providers of platform as a service. First, we define use case to add current user information from one platform as a service offer to the application hosted on another offer. To address interoperability problems, the ontology driven data mediation will be used and tested in this use case. Remote vendors' APIs are implemented as web services. Resulting web operations and their inputs/outputs are semantically annotated using cross-PaaS concepts from the developed platform as a service OWL ontology. Next, SAWSDL and XSLT are used to define service type mappings. Actual composition of platform as a service APIs is implemented by means of AI planner and developed Java web application. Testing and validation was performed on a case where current Salesforce's user is added to data container in Vosao content management system deployed on Google App Engine. Novelty of the paper is a specific application domain (composition of operations defined in PaaS APIs) and new algorithm for identification of interoperability problems.

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“…Such as, aspect-oriented programming (Bergmans, 2003), database (Sattler et al, 2003;Sudha and Jinsoo, 2004), model-based development (Reiter and Altmanninger, 2007), Web services (Nagarajan et al, 2006;Nagarajan and Verma, 2007;Ying et al, 2008;Li et al, 2009) and so on.…”

Section: Related Workmentioning

confidence: 99%

Semantic Conflicts Detection of Heterogeneous Messages of Web Services: Challenges and Solution

Al-Baltah

Ghani

Rahman

et al. 2014

Journal of Computer Science

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Service Oriented Architecture (SOA) is a new design style that has promised to alleviate the semantic interoperability problem between Web services. Exchanging the messages seamlessly between heterogeneous Web services is required but, it is still difficult due to data heterogeneity. As a result, a noticeable number of works has been proposed with the aim of solving this problem, but yet, the problem has not been solved efficiently. Furthermore, it is important to observe the lack of sufficient approaches in the state of the art, whose purposes are semantic conflicts detection between heterogeneous messages of Web services. It is for these reasons we take a step back to the detection step before providing the solution. This study proposes a new ontology-based approach that aim at detecting semantic conflicts between heterogeneous messages of Web services. The main purposes of this approach are to detect any conflict types between the messages during message exchange process and to identify the conflict type for each detected conflict. The proposed approach plays as a vital step for improving the semantic interoperability between heterogeneous Web service messages, since it facilitate the process of addressing semantic conflicts. A real scenario was used in order to demonstrate the feasibility of the proposed approach.

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Reconciling Semantic Heterogeneity in Web Services Composition

Abstract: Service Oriented Computing (SOC) is a popular computing paradigm for the development

Cited by 21 publications

References 30 publications

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Service-Level Interoperability Issues of Platform as a Service

Semantic Conflicts Detection of Heterogeneous Messages of Web Services: Challenges and Solution

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