论文部分内容阅读
Software-defined networking(SDN) is a new approach to configure and operate programmable switches of the networks(especially the data center networks) through a centralized software controller. Elephant flows normally exist in data center networks and take up a large amount of network bandwidth, so the elephant flow detection is very important to ease network congestion. A two-phase real-time detection(TPEFD) method was proposed to detect the elephant flows in the SDN-based network. First, the controller obtained aggregated statistics and shrank sample scope until it was small enough, packets were sampled in the scope in switches. In order to identify the elephant flows, the sFlow sampling results were compared with the dynamic threshold. If the sampling value exceeded the threshold value, the flow was recognized as an elephant flow. The efficiency of our method in an SDN experimental environment was evaluated. The experimental results indicated that the proposed method was feasible and the detection time was efficient.
Software-defined networking (SDN) is a new approach to configure and operate programmable switches of the networks (especially the data center networks) through a centralized software controller. Elephant flows normally exist in data center networks and take up a large amount of network bandwidth , so the elephant flow detection is very important to ease network congestion. A two-phase real-time detection (TPEFD) method was proposed to detect the elephant flows in the SDN-based network. First, the controller obtains aggregated statistics and shrank samples scope until it was small enough, packets were sampled in the scope in switches. The order was identify the elephant flows, the sFlow sampling results were compared with the dynamic threshold. The efficiency of our method in an SDN experimental environment was evaluated. The experimental results indicated that the proposed method was feasible an d the detection time was efficient.