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A Multi-Objective ACS Algorithm to Optimize Cost, Performance, and Reliability in the Cloud

Adnan Ashraf, Benjamin Byholm, Ivan Porres, A Multi-Objective ACS Algorithm to Optimize Cost, Performance, and Reliability in the Cloud. In: Omer Rana, Manish Parashar (Eds.), 8th IEEE/ACM International Conference on Utility and Cloud Computing, 341–347, IEEE, 2015.

http://dx.doi.org/10.1109/UCC.2015.54

Abstract:

In this paper, we present a novel Multi-Objective Ant Colony System algorithm to optimize Cost, Performance, and Reliability (MOACS-CoPeR) in the cloud. The proposed algorithm provides a metaheuristic-based approach for the multi-objective cloud-based software component deployment problem. MOACS-CoPeR explores the search-space of architecture design alternatives with respect to several architectural degrees of freedom and produces a set of Pareto-optimal deployment configurations. We also present a Java-based implementation of our proposed algorithm and compare its results with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). We evaluate the two algorithms against a cloud-based storage service, which is loosely based on a real system.

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BibTeX entry:

@INPROCEEDINGS{inpAsByPo15a,
  title = {A Multi-Objective ACS Algorithm to Optimize Cost, Performance, and Reliability in the Cloud},
  booktitle = {8th IEEE/ACM International Conference on Utility and Cloud Computing},
  author = {Ashraf, Adnan and Byholm, Benjamin and Porres, Ivan},
  editor = {Rana, Omer and Parashar, Manish},
  publisher = {IEEE},
  pages = {341–347},
  year = {2015},
  keywords = {Multi-objective optimization, software component deployment, ant colony system, cloud computing},
}

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

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