Optical Fiber Network Path Optimization Design for Data Classification Cloud Computing

  • Jiaojie Yuan, Jie Peng, Jiewen Zhao

Abstract

Improving the efficiency of network communication without changing the original optical fiber network hardware equipment is an important topic of network optimization technology, and it is also a research hotspot of existing network optimization in recent years. In order to reduce the probability of network congestion and improve the utilization of network resources, the data priority level and transmission path are analyzed from two aspects, and the optical fiber network path optimization model based on data classification cloud computing is designed. The optimization function mainly uses the least time cost classification and the least weighted routing scheme to filter the communication data level and type, and finally achieve the goal of optimal network communication indicators. The experiment conducted a simulation analysis of data communication between domains in four typical communication situations. The results showed that the optimized priority index increased from 0.0207 to 0.0992, the blocking probability decreased by about 1/2, and the average resource utilization increased by 5.96%. . The path optimization of this classified cloud computing model can improve the transmission efficiency of the inter-domain optical fiber network.

How to Cite
Jiaojie Yuan, Jie Peng, Jiewen Zhao. (1). Optical Fiber Network Path Optimization Design for Data Classification Cloud Computing. Forest Chemicals Review, 92-101. Retrieved from http://www.forestchemicalsreview.com/index.php/JFCR/article/view/1110
Section
Articles