36,077 research outputs found

    VOLARE: Adaptive Web Service Discovery Middleware for Mobile Systems

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    With the recent advent and widespread use of smart mobile devices, the flexibility and versatility offered by Service Oriented Architecture's (SOA) makes it an ideal approach to use in the rapidly changing mobile environment. However, the mobile setting presents a set of new challenges that service discovery methods developed for nonmobile environments cannot address. The requirements a mobile client device will have from a Web service may change due to changes in the context or the resources of the client device. In a similar manner, a mobile device that acts as a Web service provider will have different capabilities depending on its status, which may also change dramatically during runtime. This paper introduces VOLARE, a middleware-based solution that will monitor the resources and context of the device, and adapt service requests accordingly. The same method will be used to adapt the Quality of Service (QoS) levels advertised by service providers, to realistically reflect each provider's capabilities at any given moment. This approach will allow for more resource-efficient and accurate service discovery in mobile systems and will enable more reliable provider functionality in mobile devices

    Enforcing reputation constraints on business process workflows

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    The problem of trust in determining the flow of execution of business processes has been in the centre of research interst in the last decade as business processes become a de facto model of Internet-based commerce, particularly with the increasing popularity in Cloud computing. One of the main mea-sures of trust is reputation, where the quality of services as provided to their clients can be used as the main factor in calculating service and service provider reputation values. The work presented here contributes to the solving of this problem by defining a model for the calculation of service reputa-tion levels in a BPEL-based business workflow. These levels of reputation are then used to control the execution of the workflow based on service-level agreement constraints provided by the users of the workflow. The main contribution of the paper is to first present a formal meaning for BPEL processes, which is constrained by reputation requirements from the users, and then we demonstrate that these requirements can be enforced using a reference architecture with a case scenario from the domain of distributed map processing. Finally, the paper discusses the possible threats that can be launched on such an architecture

    An Intelligent QoS Identification for Untrustworthy Web Services Via Two-phase Neural Networks

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    QoS identification for untrustworthy Web services is critical in QoS management in the service computing since the performance of untrustworthy Web services may result in QoS downgrade. The key issue is to intelligently learn the characteristics of trustworthy Web services from different QoS levels, then to identify the untrustworthy ones according to the characteristics of QoS metrics. As one of the intelligent identification approaches, deep neural network has emerged as a powerful technique in recent years. In this paper, we propose a novel two-phase neural network model to identify the untrustworthy Web services. In the first phase, Web services are collected from the published QoS dataset. Then, we design a feedforward neural network model to build the classifier for Web services with different QoS levels. In the second phase, we employ a probabilistic neural network (PNN) model to identify the untrustworthy Web services from each classification. The experimental results show the proposed approach has 90.5% identification ratio far higher than other competing approaches.Comment: 8 pages, 5 figure
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