Dynamic Traffic Scheduling and Congestion Control across Data Centers Based on SDN

Abstract

Software-defined Networking (SDN) and Data Center Network (DCN) are receiving considerable attention and eliciting widespread interest from both academia and industry. When the traditionally shortest path routing protocol among multiple data centers is used, congestion will frequently occur in the shortest path link, which may severely reduce the quality of network services due to long delay and low throughput. The flexibility and agility of SDN can effectively ameliorate the aforementioned problem. However, the utilization of link resources across data centers is still insufficient, and has not yet been well addressed. In this paper, we focused on this issue and proposed an intelligent approach of real-time processing and dynamic scheduling that could make full use of the network resources. The traffic among the data centers could be classified into different types, and different strategies were proposed for these types of real-time traffic. Considering the prolonged occupation of the bandwidth by malicious flows, we employed the multilevel feedback queue mechanism and proposed an effective congestion control algorithm. Simulation experiments showed that our scheme exhibited the favorable feasibility and demonstrated a better traffic scheduling effect and great improvement in bandwidth utilization across data centers.

Improvement of 5G Transportation Services with SDN-Based Security Solutions and beyond 5G

“…Mobile data traffic is increasing with mobile users, but managing dynamic data traffic and network planning requires an intelligent solution [15]. Designing a cell association and traffic-offloading algorithm in real-time traffic measurement may be the ultimate solution for improving traffic problems.…”

Traffic-aware adaptive server load balancing for software defined networks

“…The performance of a switch can be analysed with the help of queuing models [20,21]. The challenges of wireless network virtualization [22] In the floodlight controller [23,24], there are few traditional load balancing algorithms available. They are RR approach, weight induced RR method, and statistical method.…”

Weight Queue Dynamic Active Queue Management Algorithm

“…The proposed algorithm updates both the max threshold and doublemax threshold, according to Equations (5)- (7). The updating processes stabilize the value of aql near min threshold to prevent the router buffer growing rapidly and overflowing, which leads to little packets being dropped: max_threshold = max_threshold − 2 × min _threshold (5) Doublemax_threshold = Doublemax_threshold − 2 × min _threshold (6) max_threshold = max_threshold + Min _threshold (7) As such, if aql is less than the min threshold, no update occurs for the value of max threshold and doublemax threshold. Also, if the value of aql is still less than min threshold × 2 and the max threshold position arrives at the value >= min threshold ×.…”

“…As a result, the amount of data transferred across the network devices, such as computers and routers, greatly increases. To share the network resources [2][3][4][5][6], the transferred data are divided into packets. Every device that generates packets must be temporarily stored at the router buffer before forwarding to the next router or its destination.…”