Software-Defined Congestion Control Algorithm for IP Networks

Hu, Yao; Peng, Ting; Zhang, Lianming

doi:10.1155/2017/3579540

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…The emergence of software-defined networking (SDN) [3][4][5][6][7][8][9] provides a new way to thoroughly solve this problem. Its main idea is to decouple the control function of the forwarding function of the network and hand over the control to the centralized controller.…”

Section: Background and Motivationmentioning

confidence: 99%

Terminal handover in software-defined WLANs

Chen

Duan

Zhang

2020

J Wireless Com Network

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With the development of wireless LAN (WLAN) technology, wireless access points (APs) are deployed increasingly more and the number of mobile terminals is increasing. It is normal for a mobile terminal to hand over its AP. The traditional terminal handover method cannot effectively control the handover delay and balance the network load due to the inherent drawbacks such as closed encapsulation and the lack of centralized control. In this paper, we introduce the innovative network architecture of software-defined networking (SDN), propose a software-defined WLAN architecture, and propose a seamless handover method and a load balancing handover method of the softwaredefined WLAN. Experimental results show that the proposed handover method effectively reduces the handover delay, balances the network load, and improves the quality of service (QoS) and resource utilization of the network.

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Section: Background and Motivationmentioning

confidence: 99%

Terminal handover in software-defined WLANs

Chen

Duan

Zhang

2020

J Wireless Com Network

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“…Networking. SDN is a new type of network architecture, and it is derived from the idea of network abstraction [21][22][23][24][25][26][27][28], which separates the network and consists of the control layer and data layer so that the controller can obtain global views, topology structure, network state information, etc. e data layer is mainly responsible for forwarding, decoupling the traditional tightly coupled network equipment, providing centralized management and dynamic maintenance of the distributed network, optimizing the network management, and making the network framework more flexible and agile.…”

Section: Software-definedmentioning

confidence: 99%

Elephant Flow Detection Mechanism in SDN-Based Data Center Networks

Tang

Zhang

Dong

et al. 2020

Scientific Programming

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Aiming at the problem of network congestion and unbalanced load caused by a large amount of data capacity carried in elephant flow in the data center network, an elephant flow detection method based on SDN is proposed. This method adopts the autodetect upload (ADU) mechanism. ADU is divided into two parts: ADU-Client and ADU-Server, in which ADU-Client runs in the host computer and ADU-Server runs in the SDN controller. When the host sends the elephant flow, the ADU-Client generates a packet with forged source IP address and triggers the Packet_in message of the edge switch to report the information of the elephant flow to the SDN controller and the ADU-Server completes the elephant flow identification. Experimental results show that the ADU elephant flow detection mechanism can effectively detect elephant flow in the data center network, reduce detection time, and improve network performance.

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“…However, these studies do not look at the impact of different business types on resource allocation and routing performance. Our previous works focused on a routing algorithm in a large-scale SDN [30] and a softwaredefined congestion control algorithm for IP networks [31].…”

Section: B Basics: Qos Routing Based On the Sdnmentioning

confidence: 99%

Centralized QoS Routing Using Network Calculus for SDN-Based Streaming Media Networks

Zhu

Sun

et al. 2019

IEEE Access

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Streaming media transmission requires strict quality of service (QoS) parameters such as maximum delay and delay jitter. An effective streaming media routing algorithm is a key factor in ensuring QoS. The existing solution only considers a single parameter indicator in the performance parameters such as bandwidth, delay, and utilization of the link, and fails to comprehensively measure the data flow in the network. It is not possible to comprehensively measure the relationship between the business attributes and the QoS parameters. Firstly, the deterministic upper bounds of QoS parameters in streaming media networks are solved by using network calculus theory, and the QoS parameters are normalized, and a multi-constrained QoS resource allocation model is established; the separation of control and forwarding planes is defined by using software-defined networking (SDN) to deploy the multi-constrained QoS resource allocation model in the control plane; the QoS routing system of streaming media network based on the SDN is designed and implemented, including flow table scheduling model, routing function, measurement and forwarding modules. In the routing function module of the SDN controller, a multi-constrained QoS routing algorithm based on network calculus is implemented. Experimental results show that the proposed multi-constrained QoS resource allocation model based on network calculus and the multi-constrained centralized QoS routing algorithm based on the SDN have good performance. INDEX TERMSSDN, network calculus, streaming media, multi-constrained QoS, centralized QoS routing. I. INTRODUCTION A. MOTIVATION: QOS OF STREAMING MEDIA

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Software-Defined Congestion Control Algorithm for IP Networks

Cited by 10 publications

References 17 publications

Terminal handover in software-defined WLANs

Terminal handover in software-defined WLANs

Elephant Flow Detection Mechanism in SDN-Based Data Center Networks

Centralized QoS Routing Using Network Calculus for SDN-Based Streaming Media Networks

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