Adel Boukhadra

Efficient distributed discovery and composition of OWL-S process model in P2P systems

AbstractSemantic Web services (SWs) has become the most dominant paradigm of the service-oriented computing and one of the hot issues in the area of distributed computing technology to perform business services composition more efficiently and effectively for a number of years now. The distributed composition of SWs according to their functionality increases the capability of an application to fulfill the user’s requirements. In this paper, we describe an efficient approach for improving the performance and effectiveness of automatic and cooperative composition of SWs in P2P systems. It implements a distributed solution based on scalable epidemic algorithm to discover and compose SWs in P2P systems. The main idea of our approach is to develop hybrid matching technique that operates on OWL-S process models in order to ensure high recall, further reduce the number of messages exchanged and reduce the execution time for discovering and composing SWs in the P2P network. Moreover, our matching technique is able to detect complex matching between these SWs based on their parameters and the user request. We propose a similarity measure that will be used to compose new discovered and heterogeneous collaborative Web services of large-scale distributed systems in a P2P network for satisfying user requirements, and to rank the results according to a similarity score expressing the affinities between each of them and a user-submitted query. The experimental results show that our approach is efficient and able to reduce considerably the execution time and message overhead, while preserving high levels of the distributed discovery and composition of SWs on large-size P2P networks.

Ranked Matching of OWL-S Process Model for Distributed Discovery of SWs in P2P Systems

Semantic Web services (SWs) and P2P computing have emerged as new paradigms for solving complex problems by enabling large-scale aggregation and sharing of distributed computational resources. In this paper, we present a scalable approach based on epidemic discovery algorithm to discover new distributed and heterogeneous collaborative applications of large-scale distributed systems in a P2P network, and to rank the results according to a similarity score expressing the affinities between each of them and a user-submitted query. In order to reduce the execution time and improve the applicability of the epidemic discovery algorithm for discovering SWs, we propose the matching of ontology OWL-S process model in the heart of this algorithm which reduces the search space while keeping an acceptable matching quality level. Moreover, our matching approach is able to detect complex mappings between OWL-S process models based on their parameters. Experiments showed that the matching technique reduces considerably the execution time, maintaining at the same time a good quality of the distributed discovery of SWs in a P2P network.

Hybrid Ontology-Based Matching for Distributed Discovery of SWS in P2P Systems

Semantic Web services (SWs) paradigm is considered as the most dominant technology of the Service-Oriented Computing (SOC). SWs have emerged as a major technology for deploying automated interactions between distributed and heterogeneous applications. This computing technology can be used to discover new distributed and heterogeneous collaborative applications of large-scale distributed systems in P2P systems. In this paper, we present a scalable P2P approach for distributed discovery of SWs. In this approach, we define a distributed solution based on epidemic discovery algorithm to achieve a specific goal through the distributed discovery of SWs in P2P networks. In order to improve the applicability of the epidemic discovery algorithm for discovering SWs, we propose the matching of ontology OWL-S in the heart of this algorithm which reduces the search space while keeping an acceptable matching quality level. Our matching approach relies on the use of several similarity metrics. Moreover, our matching approach is able to detect complex mappings between activities based on their parameters of OWL-S.

HPS5DSWS: A Hybrid P2P Strategy of the Distributed Discovery Mechanism for Semantic Web Services

Web services are the new generation of distributed software components. They are important for deploying automated interactions between distributed and heterogeneous applications of large-scale distributed systems. But with the evolution of the number of services available on the Web, in organizations and their large-scale use, a discovery mechanism of such a Web service in a distributed and heterogeneous environment has become a real challenge. In this paper, we describe a scalable P2P approach for automatic discovery of Semantic Web services (SWs), which supports the complexity of both SWs and task. Our architecture is based on P2P technology that has proven its effectiveness and robustness as distributed system. The particularity of our approach is to place the alignment of OWL-S in the heart of this architecture.

Efficient P2P Approach for a Better Automation of the Distributed Discovery of SWs

In this paper, we present a scalable approach for visualizing and browsing the search space of available Web services to effectively and efficiently resolve the problem of distributed discovery for Semantic Web services (SWs). We investigate the use of matching technique of ontologies OWL-S, an approach to provide a collaborative mechanism to discover basic SWs distributed among all peers in a purely distributed and heterogeneous P2P network. Our scalable approach is based on the matching technique of OWL-S in order to reduce the time complexity of the distributed discovery for SWs with respect to their semantic similarity, to simplify the management of the P2P network, to optimize the ratio of service exchange and to ensure the quality of service. The network peers offer their SWs to other ones in a distributed and heterogeneous P2P computing, and are able to use distant services to improve system responses to requests by the system that are asked. The experimental results show that the proposed approach enhances the network scalability while providing good overall performances. Also, we show that our approach can perform more effective and efficient distributed discovery of SWs with low cost in P2P computing.

A Dynamic Model to enhance the Distributed Discovery of services in P2P Overlay Networks

In Service Computing (SC), online Semantic Web services (SWs) is evolving over time and the increasing number of SWs with the same function on the Internet, a great amount of candidate services emerge. So, efficiency and effectiveness has become a stern challenge for distributed discovery to tackle uniformed behavior evolution of service and maintain high efficiency for large-scale computing. The distributed discovery of SWs according to their functionality increases the capability of an application to fulfill their own goals. In this paper, we describe an efficient and an effective approach for improving the performance and effectiveness of distributed discovery of SWs in P2P systems. As most Web services lack a rich semantic description, we extend the distributed discovery process by exploiting collaborative ranking to estimate the similarity of a SWs being used by existing hybrid matching technique of OWL-S (Ontology Web Language for Services) process models in order to reduce costs and execution time. We mapped our distributed discovery of OWL-S process models by developing a real application based on Gamma Distribution; a technique used to decrease the bandwidth consumption and to enhance the scalability of P2P systems. The particularity of the Gamma Distribution is then integrated for disseminating request about the P2P networks to perform quality based ranking so that the best SWs can be recommended first. The experimental result indicates that our approach is efficient and able to reduce considerably the execution time and the number of message overhead, while preserving high levels of the distributed discovery of SWs on large-size P2P networks.

Similarity Flooding for Efficient Distributed Discovery of OWL-S Process Model in P2P Networks☆

Abstract Due the increasing number of published Semantic Web services (SWs) rendered the distributed discovery within repositories a critical issue and a major problem that can reduce the capability and functionality of SWs in terms of efficiency and scalability. Peer-to-Peer (P2P) computing is considered as the most dominant technology to discover new distributed and heterogeneous collaborative applications for SWs. In this paper, we propose an efficient approach for improving the performance and effectiveness of automatic and cooperative discovery of large-scale distributed systems in the unstructured P2P networks. The approach exploits a scalable epidemic algorithm that uses different sources of network knowledge, such as exponential distribution, to fulfill the users requirements in order to ensure high recall, further reduce the number of messages exchanged and reduce the execution time for discovering SWs in the unstructured P2P network. In order to improve the applicability of the scalable epidemic algorithm for discovering SWs, we propose the semantic matching of OWL-S process model which improves the recall while keeping an acceptable matching quality level. The experimental results show that our efficient approach is able dynamically to adapt to network changes and preserve high levels of recall.

Towards Efficient and Effective Distributed Discovery of SWs in P2P Overlay Networks

In this paper, we will focus on the contribution an efficient and an effective approach for a distributed discovery of Semantic Web services (SWs), which address some aspects, related to problems the time complexity of collaboration in the process of automatic discovery for SWs in order to achieve adaptability in a highly-dynamic distributed computing. For this purpose, our approach is based on P2P computing that proved to be scalable, efficient and robust solutions for distributed discovery of SWs. Indeed, we propose a matching technique of ontology OWL-S process model, in order to efficiently and effectively discover appropriate Web services distributed among all peers in a large-size P2P network. For improving performance and effectiveness, our scalable approach is mapped on unstructured P2P networks by exploiting Pareto efficiency to reduce considerably the execution time and message exchanged for disseminating request about the unstructured P2P network structure among the peers, to simplify the management of the P2P network and to ensure the quality of service. The experimental results show that the proposed approach enhances the network scalability while providing good overall performances. Also, we show that our approach can perform more efficient and effective distributed discovery of SWs with low computational cost in terms of completeness and accuracy in P2P computing, when compared to the other approaches.