Latency-Aware, Static, and Dynamic Decision-Tree Placement Algorithm for Containerized SDN-VNF in OpenFlow Architectures

Gedia, Dewang; Perigo, Levi

doi:10.1109/nfv-sdn47374.2019.9039973

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…To adapt to these heterogeneous demands in various scenarios [7], network function virtualization (NFV) has been introduced [8], [9]. NFC may make IoT resource allocation more flexible, providing great scalability and autonomy for IoT service development and deployment [10], [11]. One potential application of NFV is Service Function Chaining (SFC) [12], which dynamically links multiple Virtual Network Functions (VNFs), e.g., name service, firewall, deep packet inspection, etc.…”

Section: Introductionmentioning

confidence: 99%

To Deploy New or to Deploy More?: An Online SFC Deployment Scheme at Network Edge

Yuan

Luo

Guo

et al. 2024

IEEE Internet Things J.

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Service Function Chaining (SFC) dynamically links multiple Virtual Network Functions (VNFs) to provide flexible and scalable network services for network entities and users. Implementing SFCs at the network edge provides instant VNF service yet is confined by the limited edge resources. Existing strategies suggest either to deploy new VNFs for diverse service provision or to deploy more installed VNFs for reliable service provision. However, these one-sided optimizations fail to realize comprehensive improvements in the network service quality. To this end, the motivation of this paper is to consider a more comprehensive SFC deployment plan to provide more efficient network services. In this paper, we propose DeepSFC, an online SFC deployment scheme at network edge. Our DeepSFC considers the impact of resource allocations and deployment locations on the average latency of overall service requests. It realizes an elegant trade-off between the diversity and the availability of SFCs by adopting the Deep Reinforcement Learning (DRL) method. To be specific, we first determine the type and number of VNFs that need to be deployed. Thereafter, we optimize the deployment locations of these chosen VNFs in the service chain, considering the impact of dynamic bandwidth in the real network. For more general scenarios wherein users' service requirements change or the deployed server crashes, we further relocate the VNF deployment with the joint consideration of performance degradation and migration cost. Evaluation results show that DeepSFC outperforms its competitors in various experimental settings and responds the requests with lower average latency.

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Section: Introductionmentioning

confidence: 99%

To Deploy New or to Deploy More?: An Online SFC Deployment Scheme at Network Edge

Yuan

Luo

Guo

et al. 2024

IEEE Internet Things J.

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“…As the control plane functionalities of network devices are moved to the logically centralized controller in SDN, it is crucial to guarantee the non-stop operation and sufficient processing capability of the controller. Network function virtualization (NFV) has been shown to be a viable solution for SDN controllers that require elastic infrastructure resources [1] [2] [3]. In addition, by using network virtualization technologies (virtual machines (VM), containers) and creating the SDN controller as a virtual network function (VNF), the failure of SDN controllers can be seamlessly mitigated, because, if the SDN controller is a container or VM hosted in a virtualized server environment, then failures can be reduced due to the redundant nature of the virtualized infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

IJNGN

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Software-defined Networking (SDN) is a revolutionary network architecture whose benefits stem partly from separating the data plane and control plane. In this scheme, the control functionalities are relocated to a logically centralized SDN controller which makes efficient and globally optimal forwarding decisions for network devices. Despite the fact that network virtualization technologies enable elastic capacity engineering and seamless fault recovery of the SDN controller, an optimal controller placement strategy that can adapt to changes in networks is an important but underexplored research topic. This paper proposes a novel deep reinforcement learning-based model that dynamically and strategically adjusts the location of the controller to minimize the OpenFlow latency in a virtualized environment. The experimental results demonstrate that the proposed strategy out performs both a random strategy and a generic strategy. Furthermore, this paper provides detailed instructions on how to implement the proposed model in realworld software-defined networks.

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A Comprehensive Study on 5G: RAN Architecture, Enabling Technologies, Challenges, and Deployment

Alfaqawi

Gateau

Huard

et al. 2022

Signals and Communication Technology

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Latency-Aware, Static, and Dynamic Decision-Tree Placement Algorithm for Containerized SDN-VNF in OpenFlow Architectures

Cited by 4 publications

References 21 publications

To Deploy New or to Deploy More?: An Online SFC Deployment Scheme at Network Edge

To Deploy New or to Deploy More?: An Online SFC Deployment Scheme at Network Edge

Untitled

A Comprehensive Study on 5G: RAN Architecture, Enabling Technologies, Challenges, and Deployment

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