Optimal virtualized network function allocation for an SDN enabled cloud

Leivadeas, Aris; Falkner, Matthias; Lambadaris, Ioannis; Kesidis, George

doi:10.1016/j.csi.2017.01.001

Cited by 35 publications

(18 citation statements)

References 22 publications

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“…The algorithm can find efficiently feasible and high-quality solutions in scenarios that are scaling to hundreds of VNFs. In [123], a service chain is created, consisting of a number of VNFs which facilitates a specific use case for many users and follows a multitenancy single-feature approach. A hierarchical architectural framework is proposed for the VNF placement, following the general guidelines of major standardization communities (e.g.…”

Section: Vnf Placement and The Vnf Chain Placement Problemmentioning

confidence: 99%

“…VMs) required for VNFs [161], [165], [170], more research work must be carried out in order to allow a positioning of network functions in closer proximity to service generation, and consequently provide better QoE which would benefit both ISPs and the end users. Also, only a few VNFP solutions, such as in [123], [158], [166], are applied in multiple federated clouds, while most of the surveyed works treat the problem of VNFP within only a single cloud environment (e.g., in [42], [85], [86], [90].…”

Section: Key Challenges and Lessons Learnedmentioning

confidence: 99%

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A Survey on the Placement of Virtual Resources and Virtual Network Functions

Laghrissi

Taleb

2019

IEEE Commun. Surv. Tutorials

211

110

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Cloud computing and network slicing are essential concepts of forthcoming 5G mobile systems. Network slices are essentially chunks of virtual computing and connectivity resources, configured and provisioned for particular services according to their characteristics and requirements. The success of cloud computing and network slicing hinges on the efficient allocation of virtual resources (e.g. VCPU, VMDISK) and the optimal placement of Virtualized Network Functions (VNFs) composing the network slices. In this context, this paper elaborates issues that may disrupt the placement of VNFs and VMs. The paper classifies the existing solutions for VM Placement (VMP) based on their nature, whether the placement is dynamic or static, their objectives, and their metrics. The paper then proposes a classification of VNF Placement (VNFP) approaches, first, regarding the general placement and management issues of VNFs, and second, based on the target VNF type.

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Section: Vnf Placement and The Vnf Chain Placement Problemmentioning

confidence: 99%

Section: Key Challenges and Lessons Learnedmentioning

confidence: 99%

A Survey on the Placement of Virtual Resources and Virtual Network Functions

Laghrissi

Taleb

2019

IEEE Commun. Surv. Tutorials

211

110

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“…The deployment of SCs essentially amounts to solving the problem of finding the underlying physical resources to instantiate the various VNFs comprising the SCs. A problem also known as the VNF Placement problem [11]. One major concern when solving the VNF Placement problem in such an environment is how to efficiently utilize the resources between the MEC and Cloud infrastructures in order to reconcile the conflicting goals of latency performance and deployment cost.…”

Section: Introductionmentioning

confidence: 99%

VNF Placement Optimization at the Edge and Cloud †

et al. 2019

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Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers' goal of low deployment costs.

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“…Existing works range from VNF deployment to migration mechanism, which focus on proposing suitable deployment strategies [5] and efficient migration mechanism limited by various constraints such as bandwidth [6] and node resources [7]. Many aspects for optimisation have been proposed, for instance, migration cost [8], migration time [6], and state synchronisation [9].…”

Section: Introductionmentioning

confidence: 99%