Details
Zusammenfassung: <jats:p>A small Cloud infrastructure for scientific computing likely operates in a saturated regime, which imposes to optimize the allocation of resources. Tenants typically pay <jats:italic>a priori</jats:italic> for a fraction of the overall resources. Within this business model, an advanced scheduling strategy is needed in order to optimize the data centre occupancy. FaSS, a Fair Share Scheduler service for OpenNebula, addresses this issue by satisfying resource requests according to an algorithm, which prioritizes tasks according to an initial weight and to the historical resource usage of the project. In this proceedings, we are going to describe the implementation of FaSS Version 1.0, released in March 2017 as a product of the INDIGO-DataCloud project. We are also going to discuss the results of FaSS functional and stress tests performed at the Cloud infrastructure of the INFN-Torino computing centre.</jats:p>
Umfang: 07001
ISSN: 2100-014X
DOI: 10.1051/epjconf/201921407001