Investigating decision support techniques for automating Cloud service selection

Miranda Zhang; Rajiv Ranjan; Armin Haller; Dimitrios Georgakopoulos; Peter Strazdins

doi:10.1109/CloudCom.2012.6427501

Investigating decision support techniques for automating Cloud service selection

Miranda Zhang^*, Rajiv Ranjan, Armin Haller, Dimitrios Georgakopoulos, Peter Strazdins

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

35 Citations (Scopus)

Abstract

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud-based infrastructure services (e.g. storage, network, CPU). The outcomes of this will be decision support tools and techniques, which will automate and map users' specified application requirements to Cloud service configurations.

Original language	English
Title of host publication	CloudCom 2012 - Proceedings
Subtitle of host publication	2012 4th IEEE International Conference on Cloud Computing Technology and Science
Pages	759-764
Number of pages	6
DOIs	https://doi.org/10.1109/CloudCom.2012.6427501
Publication status	Published - 2012
Event	2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012 - Taipei, Taiwan Duration: 3 Dec 2012 → 6 Dec 2012

Publication series

Name	CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science

Conference

Conference	2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012
Country/Territory	Taiwan
City	Taipei
Period	3/12/12 → 6/12/12

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10.1109/CloudCom.2012.6427501

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Zhang, M., Ranjan, R., Haller, A., Georgakopoulos, D., & Strazdins, P. (2012). Investigating decision support techniques for automating Cloud service selection. In CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science (pp. 759-764). Article 6427501 (CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science). https://doi.org/10.1109/CloudCom.2012.6427501

Zhang, Miranda ; Ranjan, Rajiv ; Haller, Armin et al. / Investigating decision support techniques for automating Cloud service selection. CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science. 2012. pp. 759-764 (CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science).

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title = "Investigating decision support techniques for automating Cloud service selection",

abstract = "The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud-based infrastructure services (e.g. storage, network, CPU). The outcomes of this will be decision support tools and techniques, which will automate and map users' specified application requirements to Cloud service configurations.",

keywords = "Cloud computing, operation research, semantic technology, service computing",

author = "Miranda Zhang and Rajiv Ranjan and Armin Haller and Dimitrios Georgakopoulos and Peter Strazdins",

year = "2012",

doi = "10.1109/CloudCom.2012.6427501",

language = "English",

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series = "CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science",

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Zhang, M, Ranjan, R, Haller, A, Georgakopoulos, D & Strazdins, P 2012, Investigating decision support techniques for automating Cloud service selection. in CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science., 6427501, CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science, pp. 759-764, 2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012, Taipei, Taiwan, 3/12/12. https://doi.org/10.1109/CloudCom.2012.6427501

Investigating decision support techniques for automating Cloud service selection. / Zhang, Miranda; Ranjan, Rajiv; Haller, Armin et al.
CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science. 2012. p. 759-764 6427501 (CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud-based infrastructure services (e.g. storage, network, CPU). The outcomes of this will be decision support tools and techniques, which will automate and map users' specified application requirements to Cloud service configurations.

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Zhang M, Ranjan R, Haller A, Georgakopoulos D, Strazdins P. Investigating decision support techniques for automating Cloud service selection. In CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science. 2012. p. 759-764. 6427501. (CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science). doi: 10.1109/CloudCom.2012.6427501

Investigating decision support techniques for automating Cloud service selection

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