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• W1507646968 abstract "Network virtualization [2] is an intriguing paradigm which loosens the ties between services and physical infrastructure. The gained flexibility promises faster innovations, enabling a more diverse Internet and ensuring coexistence of heterogeneous virtual network (VNet) architectures on top of a shared substrate. Moreover, the dynamic and demand driven allocation of resources may yield a “greener Internet” without sacrificing (or, in the presence of the corresponding migration technology: with improved!) quality-of-service (QoS) / quality-ofexperience (QoE). This paper attends to a fundamental challenge in the field of network virtualization: the flexible allocation and migration of servers. As a generic use case, we consider a network operator offering a flexible service to a set of dynamic or mobile users, and we present a model that captures the main cost factors in such a system. This allows us to shed light on the benefit of the flexible allocation and the use of migration. Although our cost model is described from a network virtualization perspective, it is not limited to such architectures: similar tradeoffs exist, e.g., in classic cloud networks, in content distribution networks, in the deployment of multicast reflectors or mirrored web content, or in cache placement. Our algorithms and insights are quite general and applicable to various scenarios, ranging from business applications such as SAP services in the cloud, to entertainment applications such as mobile gaming. Concretely, the algorithms presented in this paper guarantee a low access latency by adapting the resources over time while taking into account the corresponding costs: communication cost, allocation cost, migration cost (e.g., service interruption), and cost of running the servers. The algorithms come in two flavors, exploring the extremal perspectives: online algorithms where allocation decisions are done without any information on future requests, and offline algorithms where the (e.g., periodic) demand is known ahead of time. Both algorithms are applicable to various delay models (access latency, delay due to different load functions, etc.). Moreover, we also describe an optimal offline but static algorithm that allows us to quantify the cost-benefit tradeoffs of dynamic resource allocation, and thus to shed light on fundamental questions such as the use of migration compared to solutions using static servers. For example, our simulations show that the overall cost can be higher (by up to hundred percent), if resources are static, in particular if the demand dynamics is moderate. The content of this workshop paper is based on the longer arXiv report 1011.6594; please refer to the technical report for more details." @default.
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• W1507646968 date "2011-03-29" @default.
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• W1507646968 title "On the benefit of virtualization: strategies for flexible server allocation" @default.
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