An SDN-Based Flow Control Mechanism for Guaranteeing QoS and Maximizing Throughput

Lu, You; Fu, Baochuan; Xi, Xuefeng; Zhang, Zhancheng; Wu, Hongjie

doi:10.1007/s11277-017-4512-9

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…This solution was designed and subject to experiments in a Mininet test environment which revealed significant improvements in level of QoS performance across multiple parameters: jitter, throughput, delay, packet loss. This contribution addresses the limitations of existing methodologies to guarantee QoS performance, either through marking data-plane packets and management at the control plane automatic manager for monitoring requirements of virtual networks [8] or slice and forward methods [20]. The findings of this study demonstrate potential to address the limitations of QoS in OpenFlow's native features and protocol to support QoS [8,21,22,23].…”

Section: Discussion Of Findingsmentioning

confidence: 94%

“…To enhance QoS some research has focused on an extension of OpenFlow. The purpose of research by Lu et al [20] was to provide a solution for QoS using conventional flow control techniques and maximizing flow. A QoS slice method and forwarding mechanism is advanced nevertheless the study does not address the issue of supporting QoS in OpenFlow natively.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Design and Validation of a Meter Band Rate in OpenFlow and OpenDaylight for Optimizing QoS

Breiki¹,

Zhou²,

Luo³

2020

Adv. sci. technol. eng. syst. j.

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Technological developments in the Internet and communications have created a vastly complex and dynamic context with diverse heterogeneous networks and fast growth of mobile devices and multimedia. As the Internet becomes the primary mode of communication for many organisations there is requirement to enhance quality of service (QoS) from heterogeneous systems and networks. Traditional networks such as TETRA have become increasingly incapable of addressing the demand for media rich, bandwidth intensive traffic flows and applications. Mission-critical multimedia over new generation mobile networks face QoS constraints. This research explores a novel solution for quality of service performance for streaming mission-critical video data in OpenFlow SDN networks. A Meter Band Rate Evaluation (MBE) mechanism is advanced that improves the native QoS capability of OpenFlow and OpenDaylight. The MBE is a physical component added to the OpenFlow meter table to evaluate and dynamically adjust traffic rates and allows the traffic volume to be specified relative to other traffic in the network. Its design and development are presented, and the mechanism is verified through a simulated experiment in an SDN testbed. The results identified that QoS performance experienced a significant percentage increase when the MBE was active. These findings contribute a novel Meter Band Rate Evaluation mechanism that extends the native capability of OpenFlow and OpenDaylight to enhance the efficiency of QoS provision.

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Section: Discussion Of Findingsmentioning

confidence: 94%

Section: Related Workmentioning

confidence: 99%

Design and Validation of a Meter Band Rate in OpenFlow and OpenDaylight for Optimizing QoS

Breiki¹,

Zhou²,

Luo³

2020

Adv. sci. technol. eng. syst. j.

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“…Then, an MPLS tunnel is used to route the packets toward the egress switch and the priority of each packet specifies its output queue. Lu et al 25 . utilized preplanned network slices to both satisfy QoS requirements and maximize the overall throughput of the network.…”

Section: Related Workmentioning

confidence: 99%

Towards distributed emergency flow prioritization in software‐defined networks

et al. 2020

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SummaryEmergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software‐Defined Networking (SDN) principles allow to assign different Quality‐of‐Service (QoS) levels to different network slices.This paper proposes a microservices‐based framework, able to run both centralized and distributed, that guarantees the required bandwidth for the emergency flows and maximizes the best‐effort flows over the remaining bandwidth based on their priority. The proposed framework consists of an offline linear model, allowing to optimize the problem for a batch of flow requests. For dynamic situations, an online approach is also required in the framework to handle new incoming flows by calculating the path with a shortest path algorithm and utilizing a greedy approach in assigning bandwidth to the intermediate flows.In this article, the linear model is evaluated through simulation, the distributed architecture is evaluated through emulation while the online approach is validated through physical experiments with SDN switches. The results show that the linear model is able to guarantee the resource allocation for the emergency flows while optimizing the best‐effort flows with a sub‐second execution time. The distributed architecture is able to split up the managed network into different parts, allowing division of work between controllers. As a proof‐of‐concept, a prototype with Zodiac switches validates the feasibility of the centralized framework.

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“…We performed simulations in a grid topology where the distance between the adjacent nodes was 250 m and a random topology where nodes were deployed randomly in an area of 2.3 square kilometers. We compared the proposed slice management method with a naïve slice management (NSM) method, in which the flows belonging to each slice were routed into shortest paths, and QoS among slices was differentiated by a priority queuing [33]. In the proposed slice management method, routing as well as priority queues of slices was managed to differentiate the QoS of the slices.…”

Section: Performance Evaluationmentioning

confidence: 99%

Slice Management for Quality of Service Differentiation in Wireless Network Slicing

Kim

Park

et al. 2019

Sensors

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Network slicing is a technology that virtualizes a single infrastructure into multiple logical networks (called slices) where resources or virtualized functions can be flexibly configured by demands of applications to satisfy their quality of service (QoS) requirements. Generally, to provide the guaranteed QoS in applications, resources of slices are isolated. In wired networks, this resource isolation is enabled by allocating dedicated data bandwidths to slices. However, in wireless networks, resource isolation may be challenging because the interference between links affects the actual bandwidths of slices and degrades their QoS. In this paper, we propose a slice management scheme that mitigates the interference imposed on each slice according to their priorities by determining routes of flows with a different routing policy. Traffic flows in the slice with the highest priority are routed into shortest paths. In each lower-priority slice, the routing of traffic flows is conducted while minimizing a weighted summation of interference to other slices. Since higher-priority slices have higher interference weights, they receive lower interference from other slices. As a result, the QoS of slices is differentiated according to their priorities while the interference imposed on slices is reduced. We compared the proposed slice management scheme with a naïve slice management (NSM) method that differentiates QoS among slices by priority queuing. We conducted some simulations and the simulation results show that our proposed management scheme not only differentiates the QoS of slices according to their priorities but also enhances the average throughput and delay performance of slices remarkably compared to that of the NSM method. The simulations were conducted in grid network topologies with 16 and 100 nodes and a random network topology with 200 nodes. Simulation results indicate that the proposed slice management increased the average throughput of slices up to 6%, 13%, and 7% and reduced the average delay of slices up to 14%, 15%, and 11% in comparison with the NSM method.

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An SDN-Based Flow Control Mechanism for Guaranteeing QoS and Maximizing Throughput

Cited by 12 publications

References 9 publications

Design and Validation of a Meter Band Rate in OpenFlow and OpenDaylight for Optimizing QoS

Design and Validation of a Meter Band Rate in OpenFlow and OpenDaylight for Optimizing QoS

Towards distributed emergency flow prioritization in software‐defined networks

Slice Management for Quality of Service Differentiation in Wireless Network Slicing

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