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Optimized Deployment Plans for Platform As a Service Clouds

Benjamin Byholm, Ivan Porres, Optimized Deployment Plans for Platform As a Service Clouds. In: Geoffrey Fox, Yong Chen (Eds.), Companion Proceedings of the 10th International Conference on Utility and Cloud Computing, UCC '17 Companion, 41–46, ACM, 2017.

http://dx.doi.org/10.1145/3147234.3148112

Abstract:

We approximately solve the problem of computing deployment plans of multiple cloud services with soft real-time constraints. We recognize that this is a generalized bin packing problem with fragmentable items. We formalize the problem domain and develop an autonomous deployment planning system with soft real-time constraints. The system incorporates a genetic algorithm with quadratic worst-case time complexity for approximately solving the packing problem, providing a service deployment plan with an optimal number of servers and an approximately optimal number of service instances.

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BibTeX entry:

@INPROCEEDINGS{inpByPo17a,
  title = {Optimized Deployment Plans for Platform As a Service Clouds},
  booktitle = {Companion Proceedings of the 10th International Conference on Utility and Cloud Computing},
  author = {Byholm, Benjamin and Porres, Ivan},
  series = {UCC '17 Companion},
  editor = {Fox, Geoffrey and Chen, Yong},
  publisher = {ACM},
  pages = {41–46},
  year = {2017},
  keywords = {cloud computing, middleware, packing and covering problems},
}

Belongs to TUCS Research Unit(s): Software Engineering Laboratory (SE Lab)

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