Optimizing Resource allocation while handling SLA violations in Cloud Computing platforms

Eyraud-Dubois, Lionel; Larchevêque, Hubert

doi:10.1109/ipdps.2013.67

Cited by 27 publications

(25 citation statements)

References 20 publications

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“…To overcome these issues, proposals in the literature have considered either relaxing networking QoS by focusing only on the computing requirements [11,13] or adopting a two-phase approach [14,15,18], which first pre-selects the mapping of hosting nodes and then maps virtual links.…”

Section: Related Workmentioning

confidence: 99%

“…The authors in [11] present a Bin-packing approach that dynamically maps Virtual Machines (VMs) into Physical Machines (PMs). As a result, networking requirements are not considered in the optimization model, which may mean that QoS requirements are not met.…”

Section: Related Workmentioning

confidence: 99%

“…It is our belief that overall substrate resource use is improved if the incoming media cloud request is mapped to the MEC-DCs simultaneously for both its networking and computing requirements. Our approach, proposed in "Media edge cloud resource allocation approach" section, has two crucial improvements over related works in the literature [11][12][13][14][15][16][17][18][19][20]20]. The first improvement is a resource allocation strategy that uses the physical characteristics of the networking layer to reduce the deployment cost.…”

Section: Introductionmentioning

confidence: 99%

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Efficient resource allocation and dimensioning of media edge clouds infrastructure

et al. 2017

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Media Edge Cloud Data Centers (MEC-DCs) that are interconnected by a Metro Network were selected as infrastructure to enhance the Quality of Experience (QoE) for end users of multimedia applications. Unlike the traditional Data Centers, MEC-DCs, which are kept closer to the user, have limited availability of resources at a given Data Center. Therefore, it is of paramount importance for Infrastructure service providers to efficiently dimension and use the media resources in an environment where the applications have high resource demand and the infrastructure has limited availability. To perform this task dynamically, we first propose a resource allocation strategy that considers the physical characteristics of the networking layer while minimizing the costs of deploying media applications. Second, we analyze the different configurations of the networking layer in order to enhance the use of MEC-DCs resources and the QoE for the end-users. Simulation results show a clear advantage of this proposed optimization-based approach over the benchmarks in terms of provisioning costs, blocking ratio and resource use.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient resource allocation and dimensioning of media edge clouds infrastructure

et al. 2017

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“…In [11] a Bin packing approach is proposed to optimize the dynamic allocation of Virtual Machines (VMs) into Physical Machines (PMs). However, it only considers the allocation of required computing CPU resources.…”

Section: Related Workmentioning

confidence: 99%

“…• Bin packing [11] (BIN-IaaS), where hosting and network requirements are mapped using a Bin per type of IaaS resource, i.e., computing Bin, bandwidth Bin, Storage Bin and memory Bin.…”

Section: A Simulation Benchmarksmentioning

confidence: 99%

Column generation based-approach for IaaS aware Networked Edge Data-Centers

Jarray¹,

Salazar²,

Karmouch³

et al. 2014

2014 IEEE Globecom Workshops (GC Wkshps)

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Abstract-In this paper, our focus is on proposing a resource allocation approach for Infrastructure as Cloud Service (IaaS). Networked Edge Data-Centers (DCs) were selected as a physical infrastructure to handle IaaS Cloud requests. Doing so, we hold the potential of providing both a relatively high degree of independence between physical data centers' outages and an opportunity to reach economically IaaS cloud service users with low latency. An IaaS request is defined through two main requirements: Hosting and Networking resources. In literature, a number of works have proposed IaaS mapping approaches, however their focus was mainly on the cloud hosting requirements. Consequently, this may result in a high blocking of IaaS requests and a low utilization of resources inside the DCs due to stranding and fragmentation. To handle these drawbacks, we propose a joint optimization model of DCs and networking IaaS requirements that makes use of Column Generation technique coupled with a Branch and Bound approach in order to solve it efficiently.

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Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

2018

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Summary At the virtualized data centers, services are presented by active virtual machines (VMs) in physical machines (PMs). The manner in which VMs are mapped to PMs affects the performance of data centers and the energy efficiency. By employing the server consolidation technique, it is possible to configure the VMs on a smaller number of PMs, while the quality of service is guaranteed. In this way, the rate of active PM utilization increases and fewer active PMs would be required. Moreover, the server consolidation technique reacts to the management of underloaded and overloaded PMs by using the VM migration technology. Considering the capabilities of the server consolidation technique and its role in developing the cloud computing infrastructure, many researches have been conducted in this context. Still, a comprehensive and systematic study has not yet been performed on various consolidation techniques to check the capabilities, advantages, and disadvantages of current approaches. In this paper, a systematic study is conducted on a number of credible researches related to server consolidation techniques. In order to do so and by studying the selected works, proposed solutions are categorized based on the type of decision for running the consolidation algorithm in 4 groups of static method, dynamic method, prediction‐based dynamic method, and hybrid method. Thereafter, the advantages and disadvantages of suggested approaches are studied and compared in each research by specifying the technique and idea applied therein. In addition, by categorizing aims of researches and specifying assessment parameters, optimization approaches and type of architecture, a possibility has been provided to get familiarized with the views of the researchers.

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Optimizing Resource allocation while handling SLA violations in Cloud Computing platforms

Cited by 27 publications

References 20 publications

Efficient resource allocation and dimensioning of media edge clouds infrastructure

Efficient resource allocation and dimensioning of media edge clouds infrastructure

Column generation based-approach for IaaS aware Networked Edge Data-Centers

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

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