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"ClowdNets  are virtualized networks which can be run in parallel on top of a shared physical infrastructure. These CloudNets can have different properties (provide different security/QoS/… guarantees, run different protocols, etc.) and can be managed independently of each other. Moreover, (parts
of) a CloudNet can be migrated dynamically to locations where the service is most useful or most cost efficient (e.g., in terms of energy conservation). Depending on the circumstances and the technology, these migrations can be done live and without interrupting ongoing sessions. Furthermore CloudNets can be reprovisioned during their lifetimes to react to changing requirements or unforeseeable events.
The flexibility of the paradigm and the decoupling of the services from the underlying resource networks has many advantages; for example, it facilitates a more efficient use of the given resources, it promises faster innovations by overcoming the ossification of today's Internet architecture, it simplifies the network management, and it can improve service performance.
Currently, we address the problem of where to embed CloudNet requests, or find algorithms to migrate CloudNets to new locations (e.g., due to user mobility) taking into account the corresponding migration cost. The obtained insights are implemented in a MapReduce cluster to analyze the feasibility on real hardware. In particular the strategy to modify existing CloudNets has proven to be an interesting research question under certain consistency requirements. Moreover, the project has important economic dimensions (e.g., regarding pricing mechanisms)."
|Autor||Arora, Dushyant and Feldmann, Anja and Schaffrath, Gregor and Schmid, Stefan|
|Buchtitel||Proceedings of USENIX Workshop on Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services (Hot-ICE '11)|
|Ort||Boston, MA, USA|
|Zusammenfassung||Virtualization technology facilitates a dynamic, demand-driven allocation and migration of servers. This paper studies how the flexibility offered by network virtualization can be used to improve Quality-of-Service parameters such as latency, while taking into account allocation costs. A generic use case is considered where both the overall demand issued for a certain service (for example, an SAP application in the cloud, or a gaming application) as well as the origins of the requests change over time (e.g., due to time zone effects or due to user mobility), and we present online and optimal offline strategies to compute the number and location of the servers implementing this service. These algorithms also allow us to study the fundamental benefits of dynamic resource allocation compared to static systems. Our simulation results confirm our expectations that the gain of flexible server allocation is particularly high in scenarios with moderate dynamics.|