RT Journal Article
T1 Simplified workflow simulation on clouds based on computation and communication noisiness
A1 Mathá, Roland
A1 Ristov, Sasko
A1 Fahringer, Thomas
A1 Prodan, Radu
AB Many researchers rely on simulations to analyze and validate their researched methods on Cloud infrastructures. However, determining relevant simulation parameters and correctly instantiating them to match the real Cloud performance is a difficult and costly operation, as minor configuration changes can easily generate an unreliable inaccurate simulation result. Using legacy values experimentally determined by other researchers can reduce the configuration costs, but is still inaccurate as the underlying public Clouds and the number of active tenants are highly different and dynamic in time. To overcome these deficiencies, we propose a novel model that simulates the dynamic Cloud performance by introducing noise in the computation and communication tasks, determined by a small set of runtime execution data. Although the estimating method is apparently costly, a comprehensive sensitivity analysis shows that the configuration parameters determined for a certain simulation setup can be used for other simulations too, thereby reducing the tuning cost by up to 82.46 percent, while declining the simulation accuracy by only 1.98 percent on average. Extensive evaluation also shows that our novel model outperforms other state-of-the-art dynamic Cloud simulation models, leading up to 22 percent lower makespan inaccuracy 
PB IEEE
SN 1558-2183
YR 2020
FD 2020-07-01
LK https://hdl.handle.net/10016/30260
UL https://hdl.handle.net/10016/30260
LA eng
NO ASPIDE: Exascale programIng models for extreme data processing
NO This work was supported by the ASPIDE Project funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement No. 801091.
DS e-Archivo
RD 18 jul. 2024