Evaluating Timeliness and Accuracy Trade-offs of Supervised Machine Learning for Adapting Enterprise DRE Systems in Dynamic Environments
Several adaptation approaches have been devised to ensure end-to-end quality-of-service (QoS) for enterprise distributed systems in dynamic operating environments. Not all approaches are applicable, however, for the stringent accuracy, timeliness, and development complexity requirements of distribut...
Huvudupphovsmän: | Joe Hoffert, Douglas C. Schmidt, Aniruddha Gokhale |
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Materialtyp: | Artikel |
Språk: | English |
Publicerad: |
Springer
2011-10-01
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Serie: | International Journal of Computational Intelligence Systems |
Länkar: | https://www.atlantis-press.com/article/2364.pdf |
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