Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38890
Title: A low cost workload generation approach through the cloud for capacity planning in Service-Oriented Systems
Authors: Ferreira, C. H. G.
Estrella, J. C.
Nunes, L. H.
Reiff-Marganiec, Stephan
Batista, B. G.
Nakamura, L. H. V.
Leite, D.
Peixoto, M.
Libardi, R. M. D. O.
First Published: 25-May-2017
Presented at: IEEE International Conference on Communications 21-25 May 2017, Paris, France Bridging People, Communities, and Cultures
Start Date: 21-May-2017
End Date: 25-May-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: IEEE International Conference on Communications 21-25 May 2017, Paris, France Bridging People, Communities, and Cultures
Abstract: This paper presents a cloud approach for low cost capacity planning evaluations. To perform these evaluations we have to specify and measure the workload on the target system to discover issues and make the necessary adjustments. However, due to high costs, these evaluations are usually done using simulations, which does not consider stochastic effects. We propose to use a tool named PEESOS, a generic and flexible approach to apply real workloads and measure used resources on these real systems. As a proof of concept, our case study use a real ticket sales service to evaluate the influence of scalability in the resource provisioning to show how PEESOS can lower the cost of such real evaluations. The results show the efficiency and savings that we can obtain using PEESOS for large-scale capacity planning evaluations before the real services are deployed. This approach can avoid several problems that real services faces when they launch.
DOI Link: TBA
Links: TBA
http://hdl.handle.net/2381/38890
Embargo on file until: 1-Jan-10000
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Creative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: http://creativecommons.org/licenses/by-nc-nd/4.0/ Archived with reference to SHERPA/RoMEO and publisher website.
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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