Adaptive Traffic Engineering Based on Active Network Measurement Towards Software Defined Internet of Vehicles

With the rapid development of urbanization, enormous amounts of vehicular services have been emerging and challenge both the architectures and protocols of the Internet of Vehicles. The high-speed mobility features of nodes in the vehicular networks changes the network topology frequently, resulting in low routing efficiency, and higher packet loss. In this article, the authors utilize software-defined networking (SDN) technology to decouple the network control plane from the data forwarding plane, and divide the vehicular networks into three functional layers: data, control, application layers. Based on the proposed network architecture, the authors propose an adaptive traffic engineering (TE) mechanism to guarantee the V2V continuous traffic in vehicular networks with high-speed mobile vehicles or dynamic network topology. In particular, the proposed TE is based on a proposed active network measurement mechanism under the assistance of the centralized management ability of the SDN technique. The proposed active network measurement approach is a greedy approach where the next hop determination for the measurement packet takes multiple link reliability factors (e.g., the delay, the length, the packet error rate, the neighbors, etc.) into account. Then, the authors utilize the artificial bee colony (ABC) algorithm to optimize the TE mechanism that can be deployed and executed in the SDN controller. By the proposed TE mechanism, multiple candidate end-to-end paths can be concurrently measured, and the optimal data forwarding path can be adaptively switched. Simulation results demonstrate that the approach performs better than some recent research outcomes, especially in the aspect of performing reliable data forwarding (almost 5% better than the compared objects).

• Record URL:
  http://dx.doi.org/10.1109/TITS.2020.3028990
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2021, IEEE.
• Authors:
  • Lin, Chuan
  • Han, Guangjie
  • Du, Jiaxin
  • Xu, Tiantian
  • Peng, Yan
• Publication Date: 2021-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 3697-3706
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 22
  • Issue Number: 6
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Data communications; Networks; Software; Traffic engineering; Vehicle to vehicle communications
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01788766
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 18 2021 12:12PM