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Titlebook: Collaborative Computing: Networking, Applications, and Worksharing; 11th International C Song Guo,Xiaofei Liao,Yanmin Zhu Conference procee

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樓主: CRUST
21#
發(fā)表于 2025-3-25 03:39:49 | 只看該作者
22#
發(fā)表于 2025-3-25 08:10:20 | 只看該作者
23#
發(fā)表于 2025-3-25 13:25:41 | 只看該作者
Recovering Political Philosophyte its effectiveness with extensive experiments using OpenFlow in Mininet virtual network environment. Evaluation results show that our algorithm can achieve utility max-min fair share of bandwidth allocation for applications in datacenter networks, yet with an acceptable computational overhead.
24#
發(fā)表于 2025-3-25 18:19:42 | 只看該作者
25#
發(fā)表于 2025-3-25 20:45:44 | 只看該作者
Philosophy, Medicine, and Healthy Sexualityte operations at the same time. Moreover, a data parallel computation model is constructed to accelerate the integration of local operations. To the best of our knowledge, this is the first parallel OT algorithm. Experimental results show our proposed algorithm outperforms the stat-of-art algorithms for collaborative editing.
26#
發(fā)表于 2025-3-26 00:54:29 | 只看該作者
27#
發(fā)表于 2025-3-26 06:22:41 | 只看該作者
Achieving Application-Level Utility Max-Min Fairness of Bandwidth Allocation in Datacenter Networkste its effectiveness with extensive experiments using OpenFlow in Mininet virtual network environment. Evaluation results show that our algorithm can achieve utility max-min fair share of bandwidth allocation for applications in datacenter networks, yet with an acceptable computational overhead.
28#
發(fā)表于 2025-3-26 08:38:48 | 只看該作者
An ARM-Based Hadoop Performance Evaluation Platform: Design and Implementationcan guarantee higher computational efficiency on compute-intensive utilities with the RDD feature of Spark. Finally, we propose a more suitable theoretical hybrid architecture of future cloud clusters with a stronger master and customized ARMv8 based TaskTrackers for data-intensive computing.
29#
發(fā)表于 2025-3-26 14:25:50 | 只看該作者
Multi-core Accelerated Operational Transformation for Collaborative Editingte operations at the same time. Moreover, a data parallel computation model is constructed to accelerate the integration of local operations. To the best of our knowledge, this is the first parallel OT algorithm. Experimental results show our proposed algorithm outperforms the stat-of-art algorithms for collaborative editing.
30#
發(fā)表于 2025-3-26 18:11:11 | 只看該作者
Crowdstore: A Crowdsourcing Graph Databases can express and facilitate social collaboration, sophisticated expert discovery and low-latency crowd work. In this paper we present such an extension, CRowdPQ, backed up by the database management system Crowdstore.
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