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.

Highlights

  • Big data has become one of the hottest topics among academia and industry

  • Our proposed scheme is an attempt that first applies the multilevel feedback queue mechanism to traffic scheduling and congestion control across data centers based on Software-defined Networking (SDN), and can provide a new solution to congestion caused by the prolonged occupation of malicious flows

  • We focused on the problem of traffic scheduling and congestion control across data centers and aimed to provide an approach that could greatly improve link utilization

Read more

Summary

Introduction

Big data has become one of the hottest topics among academia and industry. With the development of big data, the amount of data from different sources such as the Internet of Things, social networking websites, and scientific research is increasing at an exponential rate [1]. Applications in SDN [9] This concentratedon onthe theproblem problem data center traffic management and attempted to. Better than traditional approaches and the SDN-based dynamically schedule flows on the link. Better than traditional approaches and the SDN-based scheme scheme with threshold value, we could improve the efficiency of the link utilizing the shortest paths. The remainder of the paper is organized as follows: In Section 2, we review the traditional network network and SDN used in data centers. We elaborate on the design and implementation of our proposed proposed scheme, DSCSD (Dynamic Scheduling and Congestion control across data centers based scheme, DSCSD (Dynamic Scheduling and Congestion control across data centers based on SDN) in Future Internet 2018, 10, 64.

Related Work
Data Center Based on Traditional Network
Data Center Based on SDN
The Design and Implementation of DSCSD
System Model andand innovated on the dataofcenter
Dynamic Traffic Scheduling
Congestion Control with Multilevel Feedback Queues
Results and and Performance
M-bandwidth
Overall
Real-time
Conclusions and Future Work
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call