QoS-Based Resource Allocation Framework for Multi-Domain SLA Management in Clouds

2013 | journal article; research paper. A publication with affiliation to the University of Göttingen.

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​QoS-Based Resource Allocation Framework for Multi-Domain SLA Management in Clouds​
Lu, K.; Yahyapour, R. ; Wieder, P.   & Kotsokalis, C. ​ (2013) 
Services Transactions on Cloud Computing1(1) pp. 1​-12​.​ DOI: https://doi.org/10.29268/stcc.2013.1.1.1 

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Authors
Lu, Kuan; Yahyapour, Ramin ; Wieder, Philipp ; Kotsokalis, Constantinos 
Abstract
In clouds, current virtualization technologies of IaaS enable the live migration of running VMs to achieve load balancing, fault‐tolerance and hardware consolidation in data centers. However, the downtime / service unavailability due to live migration may be substantial with relevance to the customers’ expectations on responsiveness, as the latter are declared in established SLAs, which define all relevant aspects of the services between service provider and customer. Moreover, the service unavailability may cause significant (potentially exponential) SLA violation penalties to its associated higher‐level domains (e.g., PaaS and SaaS). Therefore, in order to deliver high availability service, VM live migration should be arranged and managed carefully. In this paper, we present the OpenStack version of Generic SLA Manager, alongside its strategies for VM selection and allocation during live migration of VMs. Based on the proposed autonomous SLA violation‐filtering framework, we simulate a use case where IaaS (OpenStack‐SLAM) and PaaS (OpenShift) are combined; and assess performance and efficiency of the aforementioned VM placement strategies, when a multi‐domain SLA pricing & penalty model is involved. We find that our proposal is efficient in managing trade‐offs between the operational objectives of service providers (including financial considerations) and the customers’ expected QoS requirements.
Issue Date
2013
Journal
Services Transactions on Cloud Computing 
Organization
Gesellschaft für wissenschaftliche Datenverarbeitung 
Language
English

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