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- Title
A sequential Kriging method assisted by trust region strategy for proxy cache size optimization of the streaming media video data due to fragment popularity distribution.
- Authors
Li, Yaohui; Zhang, Quanyou; Wu, Yizhong; Wang, Shuting
- Abstract
The Kriging method based on machine learning is an attractive tool. In this work, a sequential Kriging method assisted by trust region strategy (SKM-TRS) is proposed to solve unconstrained black-box problems. In this SKM-TRS, the complex and expensive objective function is approximated by Kriging model. And then, a sub-optimization problem, which is constructed by Kriging and a distance factor, is minimized by the improved trust region strategy to determine next update point during each iteration cycle. The proposed method is verified by ten well-known benchmark optimization problems and a proxy cache size optimization of the streaming media video data due to fragment popularity distribution. The final test results demonstrate the efficiency and robustness of the SKM-TRS in contrast with Efficient Global Optimization (EGO), Trust Region Implementation in Kriging-based optimization with Expected improvement (TRIKE) and an Adaptive Metamodel based Global Optimization algorithm (AMGO).
- Subjects
STREAMING technology; STREAMING video &; television; KRIGING; GLOBAL optimization; BENCHMARK problems (Computer science); POPULARITY
- Publication
Multimedia Tools & Applications, 2019, Vol 78, Issue 20, p28737
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-018-6563-7