| 1. |
- Elmroth, Erik, 1964-, et al.
(författare)
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Self-management challenges for multi-cloud architectures
- 2011
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Ingår i: Towards a Service-Based Internet. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642247545 - 9783642247552 ; , s. 38-49
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Konferensbidrag (refereegranskat)abstract
- Addressing the management challenges for a multitude of distributed cloud architectures, we focus on the three complementary cloud management problems of predictive elasticity, admission control, and placement (or scheduling) of virtual machines. As these problems are intrinsically intertwined we also propose an approach to optimize the overall system behavior by policy-tuning for the tools handling each of them. Moreover, in order to facilitate the execution of some of the management decisions, we also propose new algorithms for live migration of virtual machines with very high workload and/or over low-bandwidth networks, using techniques such as caching, compression, and prioritization of memory pages.
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| 2. |
- Li, Wubin, 1983-, et al.
(författare)
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Modeling for Dynamic Cloud Scheduling via Migration of Virtual Machines
- 2011
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Ingår i: Cloud Computing Technology and Science (CloudCom). - : IEEE Computer Society. - 9781467300902 ; , s. 163-171
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Konferensbidrag (refereegranskat)abstract
- Cloud brokerage mechanisms are fundamental to reduce the complexity of using multiple cloud infrastructures to achieve optimal placement of virtual machines and avoid the potential vendor lock-in problems. However, current approaches are restricted to static scenarios, where changes in characteristics such as pricing schemes, virtual machine types, and service performance throughout the service life-cycle are ignored. In this paper, we investigate dynamic cloud scheduling use cases where these parameters are continuously changed, and propose a linear integer programming model for dynamic cloud scheduling. Our model can be applied in various scenarios through selections of corresponding objectives and constraints, and offers the flexibility to express different levels of migration overhead when restructuring an existing infrastructure. Finally, our approach is evaluated using commercial clouds parameters in selected simulations for the studied scenarios. Experimental results demonstrate that, with proper parametrizations, our approach is feasible.
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