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Realistic Workload Generation for Cloud Data Centers Bulut Veri Merkezleri icin Gercekci Is Yuku Uretimi
Date
2020-10-05
Author
Koltuk, Furkan
Schmidt, Şenan Ece
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Cite This
© 2020 IEEE.This paper proposes a new method for creating synthetic workload traces in accordance with the distribution and time characteristics of a given actual workload trace. To this end, we first find the distribution that fits to the actual workload trace, then rearrange the random samples that are generated from this distribution such that the final synthetic trace has time characteristics that are similar to the actual trace. We evaluate our method using real virtual machine and task request traces of Azure and Google cloud data centers. Our method enables generating synthetic traces that can be used for a more realistic evaluation of cloud data centers.
Subject Keywords
cloud computing, model-based workload generation, distribution fitting.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85100294960&origin=inward
https://hdl.handle.net/11511/100089
DOI
https://doi.org/10.1109/siu49456.2020.9302386
Conference Name
28th Signal Processing and Communications Applications Conference, SIU 2020
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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F. Koltuk and Ş. E. Schmidt, “Realistic Workload Generation for Cloud Data Centers Bulut Veri Merkezleri icin Gercekci Is Yuku Uretimi,” presented at the 28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Türkiye, 2020, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85100294960&origin=inward.