Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/219482
Title: Software defined traffic engineering for improving Quality of Service
Authors: Xiaoming Li;Jinyao Yan;Hui Ren
Year: 2017
Publisher: IEEE
Abstract: The Software Defined Networking (SDN) paradigm separates the control plane from the packet forwarding plane, and provides applications with a centralized view of the distributed network state. Thanks to the flexibility and efficiency of the traffic flow management, SDN based traffic engineering increases network utilization and improves Quality of Service (QoS). In this paper, an SDN based traffic scheduling algorithm called CATS is proposed to detect and control congestions in real time. In particular, a new concept of aggregated elephant flow is presented. And then a traffic scheduling optimization model is formulated with the goal of minimizing the variance of link utilization and improving QoS. We develop a chaos genetic algorithm to solve this NP-hard problem. At the end of this paper, we use Mininet, Floodlight and video traces to simulate the SDN enabled video networking. We simulate both the case of live video streaming in the wide area backbone network and the case of video file transferring among data centers. Simulation results show that the proposed algorithm CATS effectively eliminates network congestions in subsecond. In consequence, CATS improves the QoS with lower packet loss rate and balanced link utilization.
URI: http://localhost/handle/Hannan/219482
volume: 14
issue: 10
More Information: 12,
25
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8107629.pdf1.06 MBAdobe PDF
Title: Software defined traffic engineering for improving Quality of Service
Authors: Xiaoming Li;Jinyao Yan;Hui Ren
Year: 2017
Publisher: IEEE
Abstract: The Software Defined Networking (SDN) paradigm separates the control plane from the packet forwarding plane, and provides applications with a centralized view of the distributed network state. Thanks to the flexibility and efficiency of the traffic flow management, SDN based traffic engineering increases network utilization and improves Quality of Service (QoS). In this paper, an SDN based traffic scheduling algorithm called CATS is proposed to detect and control congestions in real time. In particular, a new concept of aggregated elephant flow is presented. And then a traffic scheduling optimization model is formulated with the goal of minimizing the variance of link utilization and improving QoS. We develop a chaos genetic algorithm to solve this NP-hard problem. At the end of this paper, we use Mininet, Floodlight and video traces to simulate the SDN enabled video networking. We simulate both the case of live video streaming in the wide area backbone network and the case of video file transferring among data centers. Simulation results show that the proposed algorithm CATS effectively eliminates network congestions in subsecond. In consequence, CATS improves the QoS with lower packet loss rate and balanced link utilization.
URI: http://localhost/handle/Hannan/219482
volume: 14
issue: 10
More Information: 12,
25
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8107629.pdf1.06 MBAdobe PDF
Title: Software defined traffic engineering for improving Quality of Service
Authors: Xiaoming Li;Jinyao Yan;Hui Ren
Year: 2017
Publisher: IEEE
Abstract: The Software Defined Networking (SDN) paradigm separates the control plane from the packet forwarding plane, and provides applications with a centralized view of the distributed network state. Thanks to the flexibility and efficiency of the traffic flow management, SDN based traffic engineering increases network utilization and improves Quality of Service (QoS). In this paper, an SDN based traffic scheduling algorithm called CATS is proposed to detect and control congestions in real time. In particular, a new concept of aggregated elephant flow is presented. And then a traffic scheduling optimization model is formulated with the goal of minimizing the variance of link utilization and improving QoS. We develop a chaos genetic algorithm to solve this NP-hard problem. At the end of this paper, we use Mininet, Floodlight and video traces to simulate the SDN enabled video networking. We simulate both the case of live video streaming in the wide area backbone network and the case of video file transferring among data centers. Simulation results show that the proposed algorithm CATS effectively eliminates network congestions in subsecond. In consequence, CATS improves the QoS with lower packet loss rate and balanced link utilization.
URI: http://localhost/handle/Hannan/219482
volume: 14
issue: 10
More Information: 12,
25
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8107629.pdf1.06 MBAdobe PDF