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Journal of Internet Services and Applications
Article . 2020 . Peer-reviewed
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Other literature type . 2020
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QoS-driven scheduling in the cloud

الجدولة المستندة إلى جودة الخدمة في السحابة
Authors: Giovanni Farias da Silva; Francisco Brasileiro; Raquel Lopes; Fábio Morais; Marcus Carvalho; Daniel Turull;

QoS-driven scheduling in the cloud

Abstract

Abstract Priority-based scheduling policies are commonly used to guarantee that requests submitted to the different service classes offered by cloud providers achieve the desired Quality of Service (QoS). However, the QoS delivered during resource contention periods may be unfair on certain requests. In particular, lower priority requests may have their resources preempted to accommodate resources associated with higher priority ones, even if the actual QoS delivered to the latter is above the desired level, while the former is underserved. Also, competing requests with the same priority may experience quite different QoS, since some of them may have their resources preempted, while others do not. In this paper we present a new scheduling policy that is driven by the QoS promised to individual requests. Benefits of using the QoS-driven policy are twofold: it maintains the QoS of each request as high as possible, considering their QoS targets and available resources; and it minimizes the variance of the QoS delivered to requests of the same class, promoting fairness. We used simulation experiments fed with traces from a production system to compare the QoS-driven policy with a state-of-the-practice priority-based one. In general, the QoS-driven policy delivers a better service than the priority-based one. Moreover, the equity of the QoS delivered to requests of the same class is much higher when the QoS-driven policy is used, particularly when not all requests get the promised QoS, which is the most important scenario. Finally, based on the current practice of large public cloud providers, our results show that penalties incurred by the priority-based scheduler in the scenarios studied can be, on average, as much as 193% higher than those incurred by the QoS-driven one.

Keywords

FOS: Computer and information sciences, Computer engineering. Computer hardware, Fairness, Computer Networks and Communications, TK5101-6720, Mobile QoS, Datacenter, Cloud Computing and Big Data Technologies, TK7885-7895, FOS: Economics and business, Quality of service, Service (business), FOS: Mathematics, Cloud computing, Business, Marketing, Computer network, Scheduling, Internet of Things and Edge Computing, Mathematical optimization, Blockchain and Internet of Things Integration, Cloud Computing, Computer science, Distributed computing, Service provider, Operating system, Computer Science, Physical Sciences, Telecommunication, Service classes, Scheduling (production processes), Mathematics, Information Systems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
gold