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Titlebook: Web Services – ICWS 2018; 25th International C Hai Jin,Qingyang Wang,Liang-Jie Zhang Conference proceedings 2018 Springer International Pub

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Business Objects - A New Business Process Modeling Approach process model properly. After that, the ability of BOOWM for process specification is evaluated based on a set of workflow patterns. Finally, we illustrate BOOPM approach using a crowdsourcing example and realize a prototype system to support the execution of a business process modeling by BOOPM ap
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Accelerating Training for Distributed Deep Neural Networks in MapReduce cloud resources as a web service. We also address the concern of data transmission by proposing a distributed DNN scheduler to accelerate the training time. The scheduler makes use of minimum cost flows algorithm to assign GPU resources, which considers data locality and synchronization into minimi
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Large-Scale QoS-Aware Service Composition Integrating Chained Dynamic Programming and Hybrid Pruningts show that the proposed method outperforms the state-of-the-art approach by generating solutions containing fewer services for the optimal QoS with higher efficiency and better generalization on large-scale datasets.
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Supervised Web Service Composition Integrating Multi-objective QoS Optimization and Service Quantity services without considering the QoS. Finally, a supervised multi-objective optimization is performed based on the above single-objective optimization results. Experimental results on both Web Service Challenge 2009’s datasets and substantial datasets randomly generated show that the proposed servi
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Modeling Time-Critical Processes with WED-Flowled with WED-flow into colored Petri net structures. We also show how to describe the temporal behavior of time-critical processes with time Petri nets. Therefore, we become able to reason about the functional (e.g., decide whether a certain state is definitely reached) and temporal (e.g., decide wh
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TProv: Towards a Trusted Provenance-Aware Service Based on Trusted Computing the trustworthiness of provenance information, thus TProv decreases the overhead of the huge size of provenance information and the cost of operating trusted hardware, e.g. Trusted Platform Module. The experimental results reflect TProv’s effectiveness and efficiency.
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