Portfolio scheduling for managing operational and disaster-recovery risks in virtualized datacenters hosting business-critical workloads
| Autor: | Van Beek, Vincent, Oikonomou, Giorgos, Iosup, Alexandru, Pop, Florin, Prodan, Radu, Uta, Alexandru |
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| Přispěvatelé: | Iosup, Alexandru, Prodan, Radu, Uta, Alexandru, Pop, Florin, Computer Systems, Network Institute, Massivizing Computer Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Operational Risk Cloud computing 02 engineering and technology Dynamic priority scheduling Scheduling (computing) Operational risk SDG 17 - Partnerships for the Goals 0202 electrical engineering electronic engineering information engineering Risk management Portfolio Scheduling Datacenter Resource Management Risk Management Risk Tolerance Operational Risk Disaster Recoverability Risk Risk Management business.industry Disaster recovery 020206 networking & telecommunications Risk analysis (engineering) Service level Datacenter Resource Management Risk Tolerance Disaster Recoverability Risk Portfolio 020201 artificial intelligence & image processing business Portfolio Scheduling |
| Zdroj: | Van Beek, V, Oikonomou, G & Iosup, A 2019, Portfolio scheduling for managing operational and disaster-recovery risks in virtualized datacenters hosting business-critical workloads . in A Iosup, R Prodan, A Uta & F Pop (eds), 2019 18th International Symposium on Parallel and Distributed Computing (ISPDC 2019) : [Proceedings] ., 8790949, Institute of Electrical and Electronics Engineers Inc., pp. 94-102, 18th International Symposium on Parallel and Distributed Computing, ISPDC 2019, Amsterdam, Netherlands, 5/06/19 . https://doi.org/10.1109/ISPDC.2019.00022 ISPDC Proceedings-2019 18th International Symposium on Parallel and Distributed Computing, ISPDC 2019, 94-102 STARTPAGE=94;ENDPAGE=102;TITLE=Proceedings-2019 18th International Symposium on Parallel and Distributed Computing, ISPDC 2019 |
| DOI: | 10.1109/ISPDC.2019.00022 |
| Popis: | Cloud datacenters are increasingly hosting business workloads. Such long-running, on-demand workloads raise important challenges in datacenter operation, requiring efficient online scheduling of workloads with unprecedented characteristics under strict service level agreements (SLAs). In this work, we propose an approach to manage the risk of not meeting SLAs. Our approach is based on portfolio scheduling, which is an online scheduling technique that dynamically selects a scheduling algorithm from a set (portfolio), subject to a possibly changing utility function. Ours is the first datacenter-scheduling approach to consider operational and disaster-recovery risks. Using trace-based simulation with traces collected from a commercial multi-datacenter environment, we give evidence that portfolio scheduling is able to mitigate risks significantly better than its constituent scheduling algorithms and better than datacenter engineers. |
| Databáze: | OpenAIRE |
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