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- 저자 : Ardagna, Danilo (검색결과 1 건)
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Power-aware performance analysis of self-adaptive resource management in IaaS clouds
Ataie, Ehsan,Entezari-Maleki, Reza,Etesami, Sayed Ehsan,Egger, Bernhard,Ardagna, Danilo,Movaghar, Ali North-Holland 2018 Future generations computer systems Vol.86 No.-
<P><B>Abstract</B></P> <P>In this paper, Stochastic Activity Networks (SANs) are used to model and evaluate the performance and power consumption of an Infrastructure-as-a-Service (IaaS) cloud. The proposed SAN model is scalable and flexible, yet encompasses some details of an IaaS cloud, such as Virtual Machine (VM) provisioning, VM multiplexing, and failure/repair behavior of VMs. Using the proposed SAN, a power-aware self-adaptive resource management scheme is presented for IaaS clouds that automatically adjusts the number of powered-on Physical Machines (PMs) regarding variable workloads in different time intervals. The proposed scheme respects user-oriented metrics by avoiding Service Level Agreement (SLA) violations while taking provider-oriented metrics into consideration. The behavior of the proposed scheme is analyzed when the arriving workload changes, and then its performance is compared with two non-adaptive baselines based on diverse performance and power consumption measures defined on the system. A validation of the proposed SAN model and the resource management scheme against an adapted version of the CloudSim framework is also presented.</P> <P><B>Highlights</B></P> <P> <UL> <LI> An analytical model is proposed for Infrastructure-as-a-Service (IaaS) clouds taking several details of such systems into consideration. </LI> <LI> A self-adaptive power-aware and Service Level Agreement (SLA)-aware resource management scheme is presented for cloud systems. </LI> <LI> The presented scheme adjusts the number of powered-on Physical Machines (PMs) according to the input workload. </LI> <LI> A validation of the proposed model and scheme against the CloudSim framework is presented. </LI> </UL> </P>
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