Network aware resource allocation in distributed clouds

Alicherry, Mansoor; Lakshman, T. V.

doi:10.1109/infcom.2012.6195847

Cited by 292 publications

(188 citation statements)

References 13 publications

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“…On one hand, CSPs have been expanding their presence on the territory by adding more and more data centers across the planet. Even though some of the most successful providers (e.g., Amazon EC2 11 ) have still nowadays barely one or two data centers per continent, there are other efforts towards creating way more distributed data center architectures for provisioning of cloud services [33] [34] [32], such as those leveraging "containerized" and modular data center solutions [35] [36].…”

Section: Deployment Scenariosmentioning

confidence: 99%

End-to-End Service Quality for Cloud Applications

Oberle

Cherubini

Cucinotta

2013

Economics of Grids, Clouds, Systems, and Services

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This paper aims to highlight the importance of end-to-end service quality for cloud services, with a focus on telecom carrier-grade services. In multi-tenant distributed and virtualized cloud infrastructures, the enhanced level of resource sharing raises issues in terms of performance stability and reliability of cloud services, threatening the possibility to offer precise service levels in end-to-end scenarios.

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Section: Deployment Scenariosmentioning

confidence: 99%

End-to-End Service Quality for Cloud Applications

Oberle

Cherubini

Cucinotta

2013

Economics of Grids, Clouds, Systems, and Services

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“…(For example, [9,10] offer solutions for survivable VNet embedding, but consider that the VNet is already designed and given.) Work on optimal server selection and routing of anycast services in the physical layer for intra-and inter-DC networks [11,12] do not consider resilient network design in the virtual layer.…”

Section: Related Workmentioning

confidence: 99%

Anycast end-to-end resilience for cloud services over virtual optical networks

Bùi

Jaumard

Develder

2013

2013 15th International Conference on Transparent Optical Networks (ICTON)

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Optical networks are crucial to support increasingly demanding cloud services. Delivering the requested quality of service is key to successfully provisioning end-to-end services in clouds. Therefore, as for traditional optical network services, it is of utter importance to guarantee that clouds are resilient to any failure of either network infrastructure or data centers. A crucial concept in establishing cloud services is that of network virtualization: the physical infrastructure is logically partitioned in separate virtual networks. Also, combined control of the network and data center (IT) resources is exploited. To guarantee end-to-end resilience for cloud services in such a set-up, we need to simultaneously route the services and map the virtual network, while ensuring that an alternate routing is always available. Note that the anycast routing concept applies: assigning server resources requested by the customer to a particular (physical) data center can be done transparently. This paper investigates the design of scalable optimization models to perform the virtual network mapping resiliently (for single bidirectional link failures), thus supporting resilient anycast cloud virtual networks. We compare two resilience approaches: PIP-resilience maps each virtual link to two alternate physical routes, VNO-resilience provides alternate paths in the virtual topology (while enforcing physical link disjointness).

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“…Breitgand and Epstein presented a 2-approximation algorithm for the stochastic bin packing problem under the assumption of independent normally distributed random variables [24]. Alicherry and Lakshman derived some approximation algorithms and inapproximability results for the problem of minimizing the cost of communication among VMs [25,26]. Breitgand et al devised algorithms for profit optimization in a federated cloud and proved that, under certain conditions, the algorithm for one of the sub-problems, which is a greedy LProunding procedure, ensures 2-approximation [27].…”

Section: Introduction and Previous Workmentioning

confidence: 99%

Rigorous results on the effectiveness of some heuristics for the consolidation of virtual machines in a cloud data center

Mann

2015

Future Generation Computer Systems

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Dynamic consolidation of virtual machines (VMs) in a cloud data center can be used to minimize power consumption. Beloglazov et al. have proposed the MM (Minimization of Migrations) heuristic for selecting the VMs to migrate from under-or over-utilized hosts, as well as the MBFD (Modified Best Fit Decreasing) heuristic for deciding the placement of the migrated VMs. According to their simulation results, these heuristics work very well in practice. In this paper, we investigate what performance guarantees can be rigorously proven for the heuristics. In particular, we establish that MM is optimal with respect to the number of selected VMs of an over-utilized host and it is a 1.5-approximation with respect to the decrease in utilization. On the other hand, we show that the result of MBFD can be arbitrarily far from the optimum. Moreover, we show that even if both MM and MBFD deliver optimal results, their combination does not necessarily result in optimal VM consolidation, but approximation results can be proven under suitable technical conditions. To the best of our knowledge, these are the first rigorously proven results on the effectiveness of also practically useful heuristic algorithms for the VM consolidation problem.

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Network aware resource allocation in distributed clouds

Cited by 292 publications

References 13 publications

End-to-End Service Quality for Cloud Applications

End-to-End Service Quality for Cloud Applications

Anycast end-to-end resilience for cloud services over virtual optical networks

Rigorous results on the effectiveness of some heuristics for the consolidation of virtual machines in a cloud data center

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