Effective resource provisioning for QoS-aware virtual networks in SDN

Podili, Prashanth; Kataoka, Kotaro

doi:10.1109/noms.2018.8406241

Cited by 2 publications

(4 citation statements)

References 22 publications

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“…Resource allocation has also been investigated in SDN and access control in mobile networks. Podili, P., et al [104] have introduced a resource provisioning approach for virtual networks in SDN focused on E2E delay and bandwidth. Results have shown improvements in availability, scalability (C2), and cost-effectiveness (C3).…”

Section: B Resource Allocationmentioning

confidence: 99%

“…Works on resource allocation (e.g. [104], [105]) and caching (e.g. [121], [122]) have also studied energy consumption to deliver more efficient and greener architectures.…”

Section: Open Challenges and Future Directionsmentioning

confidence: 99%

“…Orchestration practices for distributed cloud infrastructures are also gaining significant attention. Resource allocation [100][101][102][103][104][105][106][107] addresses proper service deployment, while auto-scaling [108][109][110][111] mechanisms guarantee that deployed services are sufficient to handle current network demand. Efficient provisioning strategies have been studied for vehicular networks and IoT contexts.…”

Section: A Lessons Learnedmentioning

confidence: 99%

See 2 more Smart Citations

Towards Low-Latency Service Delivery in a Continuum of Virtual Resources: State-of-the-Art and Research Directions

Santos

Wauters

Volckaert

et al. 2021

IEEE Commun. Surv. Tutorials

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Section: B Resource Allocationmentioning

confidence: 99%

“…Works on resource allocation (e.g. [104], [105]) and caching (e.g. [121], [122]) have also studied energy consumption to deliver more efficient and greener architectures.…”

Section: Open Challenges and Future Directionsmentioning

confidence: 99%

Section: A Lessons Learnedmentioning

confidence: 99%

See 1 more Smart Citation

Towards Low-Latency Service Delivery in a Continuum of Virtual Resources: State-of-the-Art and Research Directions

Santos

Wauters

Volckaert

et al. 2021

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

“…In this work we try a combination of machine learning on mobile networks from the two aspects. First, we study a transport network based on a flexible SDN network architecture, which boosts the need for low time delay on the network side [4]. Secondly, we propose a routing orchestration method embedded in machine learning, which can enhance the agility of traffic engineering [5].…”

Section: A Software Defined Networkmentioning

confidence: 99%

Intelligent Routing Orchestration for Ultra-Low Latency Transport Networks

et al. 2020

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Autonomous driving scenarios face the need for millisecond real-time response, which has led to the study of mobile networks with high speed and ultra-low latency. Software-defined networking (SDN) is recognized as a key technology for next-generation networks because it contains advanced functions such as centralized control, software-based traffic analysis, and forwarding rules for dynamic updates. In this paper, an SDN with flexible architecture is considered and a transport component is proposed. The component based on mesh topology is an example of joint route prediction and forwarding. First, different from existing transport protocols, the component can adopt a software-defined stream access control strategy that includes an extended forwarding mechanism (retransmission) to improve the shortterm response performance. Second, we evaluate the impact of route prediction on transport network performance by using offline training and prediction. The key challenge here is that a suitable model needs to be trained from a limited training sample dataset, which will dynamically update the forwarding rules based on current and historical facts (network data). By introducing a parallel neural network classifier, an intelligent route arrangement is implemented in this work. Experimental results over different traffic patterns verify the advantages of the design. Not only does it enhance the flexibility of SDN, but it also significantly reduces the signaling overhead of the transport network without reducing the network throughput.INDEX TERMS SDN, traffic control, routing, machine learning, prediction.

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Effective resource provisioning for QoS-aware virtual networks in SDN

Cited by 2 publications

References 22 publications

Towards Low-Latency Service Delivery in a Continuum of Virtual Resources: State-of-the-Art and Research Directions

Towards Low-Latency Service Delivery in a Continuum of Virtual Resources: State-of-the-Art and Research Directions

Intelligent Routing Orchestration for Ultra-Low Latency Transport Networks

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