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	Wang, Wei     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending Date Reviewed     1 - 5 of 12 reviews       H-Container: enabling heterogeneous-ISA container migration in edge computing Xing T., Barbalace A., Olivier P., Karaoui M., Wang W., Ravindran B. ACM Transactions on Computer Systems 39(1-4): 1-36, 2021.  Type: Article Xing et al. describe a novel approach to dealing with the difficulties posed by container migration in edge computing settings with heterogeneous instruction set architectures (ISAs). By putting forth a mechanism that permits effective and seamles...... May 10 2023     Big data analytics in science Wei Wang. KDD2016 video, 01:02:20, published on Apr 4, 2016, https://www.youtube.com/watch?v=JychF6WgjWk. Type: Video The presenter frequently refers to slides on a screen via hand gestures; however, except for one instance, less than one-quarter of any slide is ever visible in the video. As a result, the presented material is very difficult to follow...... Dec 5 2018     Discovering and understanding Android sensor usage behaviors with data flow analysis Liu X., Liu J., Wang W., He Y., Zhang X. World Wide Web 21(1): 105-126, 2018.  Type: Article From 2008 to 2018, the use of mobile apps has grown exponentially, reaching more than 3.8 million apps in Google’s Play Store and two million apps in Apple’s App Store, followed by numerous other apps available from...... Jul 6 2018     SINGA: putting deep learning in the hands of multimedia users Wang W., Chen G., Dinh A., Gao J., Ooi B., Tan K., Wang S.  MM 2015 (Proceedings of the 23rd Annual ACM Conference on Multimedia, Brisbane, Australia, Oct 26-30, 2015) 25-34, 2015.  Type: Proceedings Deep learning is an aspect of machine learning that attempts, through algorithms, to model complex abstractions in data. A research goal is to create architectures to achieve this with masses of uncharacterized data. This research pape...... Dec 14 2015     Using priced timed automaton to analyse the energy consumption in cloud computing environment Deng Z., Zeng G., He Q., Zhong Y., Wang W. Cluster Computing 17(4): 1295-1307, 2014.  Type: Article By accounting for the mismatch in energy consumption by different cloud servers to process the same task, this paper proposes a method to save energy. The authors introduce a priced timed automaton to model the optimization problem. In...... Jun 8 2015     Display 510152550100 per column
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