Per-Flow Routing with QoS Support to Enhance Multimedia Delivery in OpenFlow SDN

Diorio, Rafael Fernando; Timóteo, V. S.

doi:10.1145/2976796.2976844

Cited by 5 publications

(5 citation statements)

References 10 publications

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“…Diorio et al 11 uses SDN and OpenFlow to provide QoS support to multimedia data flows in a network. They propose a multimedia gateway, developed as an OpenFlow component to aid the controller.…”

Section: Related Workmentioning

confidence: 99%

“…In this sense, their solution looks like the previous works we described. [9][10][11] In fact, all four works use the SDN controller to reconfigure network (ie, routing) in an attempt to accommodate traffic with high-quality demands on better paths, like faster or short routes.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, Table 1 also associates these works with the QoS provisioning techniques that are used by each of them. x x Nam et al (2014) 10 x x Diorio et al (2016) 11 x x x HumernBrum et al (2014) 1 x x Afaq et al (2015) 12 x x Tomovic et al (2014) 15 x x x Jinyao et al (2015) 16 x x x Kotronis et al (2016) 17 x x Oliveira et al (2018) 18,19 x x…”

Section: Related Workmentioning

confidence: 99%

“…Finally, the new approach is not focused on supporting a specific application, as opposed to most of the related works. 1,[9][10][11][12] To demonstrate the feasibility of our architecture, we present three proof-of-concept experimental setups that exploit our QoS provisioning mechanism. First, we evaluate a simple scenario, in which a network administrator configures specific QoS levels to distinct file transfers.…”

Section: Introductionmentioning

confidence: 99%

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SDN‐based architecture for providing quality of service to high‐performance distributed applications

et al. 2019

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The specification of quality of service (QoS) requirements in most of the existing networks is still challenging. In part, traditional network environments are limited by their high administrative cost, although software-defined networks (SDNs), a newer network paradigm, simplify the management of the whole network infrastructure. In fact, SDN provides a simple way to effectively develop QoS provisioning mechanisms. In this sense, we explore the SDN model and its flexibility to develop a QoS provisioning architecture. Through the use of our new architecture, network operators are able to specify QoS levels in a simple way. Each individual data flow can be addressed, and the architecture we propose also negotiates the QoS requirements between the network controller and applications. On the other hand, the network controller continuously monitors the network environment. Then, it allocates network elements resources and prioritizes traffic, adjusting the network performance. We evaluate the feasibility of our QoS provisioning mechanism by presenting three experimental setups under realistic scenarios. For example, for a given scenario where we evaluate file transfers, our results indicate that the additional SDN modules present negligible overhead. Moreover, for a given setup, we observe a reduction of up to 82% in the file transfer times.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

SDN‐based architecture for providing quality of service to high‐performance distributed applications

et al. 2019

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“…The related work analysis exhibits that solutions can be categorized as based on unicast [18,19,26,27,28], in SDN Multicast [20,21,22,29,30,31,32] or in groups on SDN [24,25], according to the communication model used in the SDN data plane. The Table 1 summarizes the key features of these solutions in line with requirements, including: (i) session-level semantics, (ii) multiuser communication, (iii) quality-oriented control plan, and (iv) resilience.…”

Section: Related Workmentioning

confidence: 99%

Resilient Multiuser Session Control in Softwarized Fog-Supported Internet of Moving Thing Systems

Silva

Neto

2019

Sensors

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The combination of IoT and mobility promises to open a new frontier of innovations in smart environments, through the advent of the Internet of Moving Things (IoMT) paradigm. In IoMT, an array of IoT devices leverage IP-based mobile connectivity to provide a vast range of data ubiquitously. The IoMT realization will foster smart environments at unprecedented levels, by efficiently affording services and applications whereby today’s technologies make their efficiency unfeasible, such as autonomous driving and in-ambulance remotely-assisted patient. IoMT-supported mission-critical applications push computing and networking requirements to totally new levels that must be met, raising the need for refined approaches that advance beyond existing technologies. In light of this, this paper proposes the Resilient MultiUser Session Control (ReMUSiC) framework, which deploys emerging softwarization and cloudification technologies to afford flexible, optimized and self-organized control plane perspectives. ReMUSiC extends our previous work through the following innovations. A quality-oriented resilience mechanism is capable of responding to network dynamics events (failure and mobility) by readapting IoMT multiuser mobile sessions. A softwarized networking control plane that allows to, at runtime, both fetch current network state and set up resources in the attempt to always keep affected IoMT multiuser mobile sessions best-connected and best-served. A cloudification approach allows a robust environment, through which cloud- and fog-systems interwork to cater to performance-enhanced capabilities. The IoMT’s suitability and performance impacts by ReMUSiC framework use are assessed through real testbed prototyping. Impact analysis in Quality of Service (QoS) performance and perceived Quality of Experience (QoE), demonstrate the remarkable abilities of the ReMUSiC framework, over a related approach, in keeping IoMT multiuser mobile sessions always best-connected and best-served.

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QR-SDN: Towards Reinforcement Learning States, Actions, and Rewards for Direct Flow Routing in Software-Defined Networks

et al. 2020

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Flow routing can achieve fine-grained network performance optimizations by routing distinct packet traffic flows over different network paths. While the centralized control of Software-Defined Networking (SDN) provides a control framework for implementing centralized network optimizations, e.g., optimized flow routing, the implementation of flow routing that is adaptive to varying traffic loads requires complex models. The goal of this study is to pursue a model-free approach that is based on reinforcement learning. We design and evaluate QR-SDN, a classical tabular reinforcement learning approach that directly represents the routing paths of individual flows in its state-action space. Due to the direct representation of flow routes in the QR-SDN state-action space, QR-SDN is the first reinforcement learning SDN routing approach to enable multiple routing paths between a given source (ingress) switch-destination (egress) switch pair while preserving the flow integrity. That is, in QR-SDN, packets of a given flow take the same routing path, while different flows with the same source-destination switch pair may take different routes (in contrast, the recent DRL-TE approach splits a given flow on a per-packet basis incurring high complexity and out-of-order packets). We implemented QR-SDN in a Software-Defined Network (SDN) emulation testbed. Our evaluations demonstrate that the flow-preserving multi-path routing of QR-SDN achieves substantially lower flow latencies than prior routing approaches that determine only a single source-destination route. A limitation of QR-SDN is that the state-action space grows exponentially with the number of network nodes. Addressing the scalability of direct flow routing, e.g., through routing only high-rate flows, is an important direction for future research. The QR-SDN code is made publicly available to support this future research.

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Per-Flow Routing with QoS Support to Enhance Multimedia Delivery in OpenFlow SDN

Cited by 5 publications

References 10 publications

SDN‐based architecture for providing quality of service to high‐performance distributed applications

SDN‐based architecture for providing quality of service to high‐performance distributed applications

Resilient Multiuser Session Control in Softwarized Fog-Supported Internet of Moving Thing Systems

QR-SDN: Towards Reinforcement Learning States, Actions, and Rewards for Direct Flow Routing in Software-Defined Networks

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