DFVisor: Scalable network virtualization for QoS management in cloud computing

Liao, Liqiong; Leung, Victor C. M.; Nasiopoulos, Panos

doi:10.1109/cnsm.2014.7014186

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Other proxy-based virtualization works are proposed later on to overcome some of the limitation in FlowVisor as it is the case in OpenVirteX [254] which built based on FlowVisor to tackle the address virtualization problem. DFVisor [255], [256] attempts to enhance the flow setup time since flow setup process is intercepted by the hypervisor to make each controller think it controls the network. AutoSlice [257] proposes schemes to automate the virtual slice deployment and solve the single point of failure in a single proxy based virtualization by distributing that task which makes it scalable for a large number of users.…”

Section: B: Network Virtualizationmentioning

confidence: 99%

A Survey on Autonomic Provisioning and Management of QoS in SDN Networks

BinSahaq

Sheltami

2019

IEEE Access

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In today's Internet, killer network services and applications, such as video and audio streaming, network storage, and online video games, are pushing the network infrastructure resources to the edge. By design and for the most part, the Internet is the best offer delivery ecosystem with little or no endto-end quality-of-service (QoS) guarantees. Even, frameworks, such as IntServ and DiffServ that were designed and implemented to provide QoS guarantees, still fail to solve this problem at a wide scale. Software-defined networking (SDN) is a fast emerging networking paradigm that promises to provide endto-end QoS guaranteeing by offering greater network flexibility, abstraction, control, and programmability to network resources. In this paper, we review, survey, and discuss the current state of the art on QoS provisioning in the area of SDN, with respect to applying the concept of autonomic computing (AC) to automatically support, provision, monitor, and maintain QoS requirements. This paper includes in-depth classification, taxonomy, and comparative analysis for the autonomic-based QoS provisioning in accordance with the famous influential and widely adopted the monitor-analyze-plan-execute-knowledge (MAPE-K) IBM architectural model for autonomic computing.

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Section: B: Network Virtualizationmentioning

confidence: 99%

A Survey on Autonomic Provisioning and Management of QoS in SDN Networks

BinSahaq

Sheltami

2019

IEEE Access

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“…3) DFVisor: Distributed FlowVisor (DFVisor) [169], [170] is a hypervisor designed to address the scalability issue of FlowVisor as a centralized SDN virtualization hypervisor. DFVisor realizes the virtualization layer on the SDN physical network itself.…”

Section: Distributed Hypervisorsmentioning

confidence: 99%

Survey on Network Virtualization Hypervisors for Software Defined Networking

Blenk

Basta

Reisslein

et al. 2016

IEEE Commun. Surv. Tutorials

259

130

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Software defined networking (SDN) has emerged as a promising paradigm for making the control of communication networks flexible. SDN separates the data packet forwarding plane, i.e., the data plane, from the control plane and employs a central controller. Network virtualization allows the flexible sharing of physical networking resources by multiple users (tenants). Each tenant runs its own applications over its virtual network, i.e., its slice of the actual physical network. The virtualization of SDN networks promises to allow networks to leverage the combined benefits of SDN networking and network virtualization and has therefore attracted significant research attention in recent years. A critical component for virtualizing SDN networks is an SDN hypervisor that abstracts the underlying physical SDN network into multiple logically isolated virtual SDN networks (vSDNs), each with its own controller. We comprehensively survey hypervisors for SDN networks in this article. We categorize the SDN hypervisors according to their architecture into centralized and distributed hypervisors. We furthermore sub-classify the hypervisors according to their execution platform into hypervisors running exclusively on general-purpose compute platforms, or on a combination of general-purpose compute platforms with general-or special-purpose network elements. We exhaustively compare the network attribute abstraction and isolation features of the existing SDN hypervisors. As part of the future research agenda, we outline the development of a performance evaluation framework for SDN hypervisors.

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