A dynamic task scheduler tolerant to multiple hibernations in cloud environments

• Published in: Cluster computing Vol. 24; no. 2; pp. 1051 - 1073
• Main Authors: Teylo, Luan, Arantes, Luciana, Sens, Pierre, Drummond, Lucia M. A.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2021; Springer Nature B.V; Springer Verlag
• Subjects: Availability; Computer Communication Networks; Computer Science; Distributed, Parallel, and Cluster Computing; Energy consumption; Failure; Fault tolerance; Hibernation; Monte Carlo simulation; Operating Systems; Processor Architectures; Provisioning; Scheduling; Task scheduling; Virtual environments; Cloud computing; Monetary cost minimization; Dynamic BoT scheduling; Temporal failures; Spot VM hibernation; Dynamic BoT Scheduling; Temporal Failures; Spot VM Hibernation; Cloud Computing
• ISSN: 1386-7857; 1573-7543
• DOI: 10.1007/s10586-020-03175-2

Cloud platforms usually offer several types of Virtual Machines (VMs) with different guarantees in terms of availability and volatility, provisioning the same resource through multiple pricing models. For instance, in the Amazon EC2 cloud, the user pays per use for on-demand VMs while spot VMs are instances available at lower prices. However, a spot VM can be terminated or hibernated by EC2 at any moment. In this work, we propose the Hibernation-Aware Dynamic Scheduler (HADS) that schedules Bag-of-Tasks (BoT) applications with deadline constraints in both hibernation prone spots VMs and on-demand VMs. HADS aims at minimizing the monetary costs of executing BoT applications on Clouds ensuring that their deadlines are respected even in the presence of multiple hibernations. Results collected from experiments on Amazon EC2 VMs using synthetic applications and a NAS benchmark application show the effectiveness of HADS in terms of monetary costs when compared to on-demand VM only solutions.