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Titlebook: Advances in Services Computing; 9th Asia-Pacific Ser Lina Yao,Xia Xie,Hai Jin Conference proceedings 2015 Springer International Publishing

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樓主: Neogamist
21#
發(fā)表于 2025-3-25 04:00:46 | 只看該作者
Lecture Notes in Computer Scienceenabled cloud infrastructures by using an . (API). Using real-time data, we demonstrate that our framework can improve network resource management and is capable of handling increasing traffic requests. We also validate our framework efficiency through simulations.
22#
發(fā)表于 2025-3-25 10:25:15 | 只看該作者
A. B. Wheeler,R. S. Jones,T. N. Phillips so as to make a better trade-off between the number of available services and the accuracy of service discovery. The results of experiments conducted on a publicly available data set show that compared with other widely used methods, our approach can improve the performance of service discovery by decreasing the number of candidate services.
23#
發(fā)表于 2025-3-25 13:46:42 | 只看該作者
24#
發(fā)表于 2025-3-25 17:12:40 | 只看該作者
25#
發(fā)表于 2025-3-25 21:59:10 | 只看該作者
Transformations and Projections,every two adjacent checkpoints. Third, we reproduce the bugs according to these paths. We can decrease the logging overhead in the runtime by searching instead of logging. We have implemented the method and evaluate it on Xen. The experimental results demonstrate that our method can reduce the runtime overhead by 30?% effectively.
26#
發(fā)表于 2025-3-26 00:51:00 | 只看該作者
27#
發(fā)表于 2025-3-26 05:47:13 | 只看該作者
Modelling of design decisions for CAD,veness of our approach. The other experiment is conducted on the same dataset to assess impacts of the two constraints on service relations. Experimental results show that our approach can clarify the two types of constraints effectively and achieve adequate recall and precision. Moreover, it is ind
28#
發(fā)表于 2025-3-26 10:23:10 | 只看該作者
A. J. Beaussart,R. B. Pipes,R. K. Okinemmendation approach dubbed as CASR-UPE (Context-aware Web Services Recommendation based on User Preference Expansion). First, we model the influence of user location update on user preference. Second, we perform the context-aware similarity mining for updated location. Third, we predict the Quality
29#
發(fā)表于 2025-3-26 16:34:09 | 只看該作者
30#
發(fā)表于 2025-3-26 17:28:46 | 只看該作者
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