RISCLESS: A Reinforcement Learning Strategy to Guarantee SLA on Cloud Ephemeral and Stable Resources - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2022

RISCLESS: A Reinforcement Learning Strategy to Guarantee SLA on Cloud Ephemeral and Stable Resources

Abstract

In this paper, we propose RISCLESS, a Reinforcement Learning strategy to exploit unused Cloud resources. Our approach consists in using a small proportion of stable on-demand resources alongside the ephemeral ones in order to guarantee customers SLA and reduce the overall costs. The approach decides when and how much stable resources to allocate in order to fulfill customers’ demands. RISCLESS improved the Cloud Providers (CPs)’ profits by an average of 15.9% compared to past strategies. It also reduced the SLA violation time by 36.7% while increasing the amount of used ephemeral resources by 19.5%.
Fichier principal
Vignette du fichier
RISCLESS_A_Reinforcement_Learning_Strategy_to_Guarantee_SLA_on_Cloud_Ephemeral_and_Stable_Resourcesauthor.pdf (337.84 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03921309 , version 1 (27-04-2022)
hal-03921309 , version 2 (05-01-2023)

Licence

Identifiers

Cite

Sidahmed Yalles, Mohamed Handaoui, Jean-Emile Dartois, Olivier Barais, Laurent d'Orazio, et al.. RISCLESS: A Reinforcement Learning Strategy to Guarantee SLA on Cloud Ephemeral and Stable Resources. 2022 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Mar 2022, Valladolid, Spain. pp.83-87, ⟨10.1109/PDP55904.2022.00021⟩. ⟨hal-03921309v2⟩
105 View
70 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More