1. A two-phase heuristic algorithm for power-aware offline scheduling in IaaS clouds.
- Author
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Ignatov, A., Maslova, I., Posypkin, M., Yang, W., and Wu, J.
- Subjects
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HEURISTIC algorithms , *SCHEDULING , *ONLINE algorithms , *ALGORITHMS - Abstract
The paper aims at mitigating hot-spots during Offline Scheduling in IaaS (Infrastructure-as-a-Service) cloud systems. Unlike previous studies, the research focuses on identifying and resolving hot-spots not at servers, but at server racks. A two-phase algorithm for performing power-aware offline scheduling is proposed. The first phase aims at identifying and mitigating hot-spots at racks, while the second phase performs VM consolidation, i.e. minimization of the number of occupied servers while maintaining a feasible VM mapping and low migration costs. The proposed algorithm takes into account the dynamic nature of VM's resource consumption: it does not only resolve detected hot-spots, but also tries to avoid hot-spots in a reasonable future time period. The algorithm was tested with the data from a real IaaS cloud with different sets of algorithm's parameters. Experimental evaluation showed that the statistical estimates of the future VM's resource consumption provide the most reliable mapping, which is a result of minimization of the number of new hot-spot occurrences. • A server rack is a hot-spot if it exceeds the upper bound of power consumption. • Hot-spot identification, mitigation, and avoidance is crucial for IaaS systems. • An algorithm is proposed for rack hot-spot mitigation and consolidation of VMs. • Considering future CPU utilization values is associated with migrating more memory. • Ignoring future CPU utilization values leads to more new hot-spots happening shortly. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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