11,202 research outputs found

    Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

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    With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

    A Location Based Value Prediction for Quality of Web Service

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    The number of web services with functionality increases, the service users usually depends on web recommendation systems. Now a days the service users pay more importance on non functional properties which are also known as Quality of Service (QoS) while finding and selecting appropriate web services. Collaborative filtering approach predicts the QoS values of the web services effectively. Existing recommendation systems rarely consider the personalized influence of the users and services in determining the similarity between users and services. The proposed system is a ranking oriented hybrid approach which integrates user-based and item-based QoS predictions. Many of the non-functional properties depends on the user and the service location. The system thus employs the location information of users and services in selecting similar neighbors for the target user and service and thereby making personalized service recommendation for service users

    Adaptively improving performance stability of cloud based application using the modern portfolio theory

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    The increasing number of Software-as-a-Service(SaaS) services available in the cloud market make them plausible and attractive for building cloud-based applications. However, performance instability is common in the cloud environment due to changes in supply and demand of shared computational infrastructure and resources. Candidate services are vulnerable to such instability. Current service selection and composition approaches do not explicitly address performance fluctuations when building cloud-based applications. This thesis proposes a novel approach to improve performance stability by leveraging on the principles of design diversity and portfolio-based thinking when selecting and composing cloud-based applications. The objective is to minimize the risks that could stem from selecting and composing cloud-based services that are vulnerable to performance instability. In this thesis, we use two scenarios to illustrate the applicability and the effectiveness of the approach. As scalability is of paramount importance for efficient dynamic and adaptive selection and composition, the thesis adapt a systematic method to identify the various scalability dimensions that can affect the working of the approach and consequently evaluate the sensitivity of the approach to the identified dimensions. The thesis concludes with possible directions for future work

    E-finance-lab at the House of Finance : about us

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    The financial services industry is believed to be on the verge of a dramatic [r]evolution. A substantial redesign of its value chains aimed at reducing costs, providing more efficient and flexible services and enabling new products and revenue streams is imminent. But there seems to be no clear migration path nor goal which can cast light on the question where the finance industry and its various players will be and should be in a decade from now. The mission of the E-Finance Lab is the development and application of research methodologies in the financial industry that promote and assess how business strategies and structures are shared and supported by strategies and structures of information systems. Important challenges include the design of smart production infrastructures, the development and evaluation of advantageous sourcing strategies and smart selling concepts to enable new revenue streams for financial service providers in the future. Overall, our goal is to contribute methods and views to the realignment of the E-Finance value chain. ..
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