A Performance Study of Flow-Based Monitoring in Internet of Vehicles

Abstract

The Internet of Vehicles (IoV) sustains the ubiquitous communications and diverse services among vehicles throughout the Internet access, which would generate a huge volume of data. Acquired through network monitoring, such big data can be further utilized for IoV management. However, the dynamic scenarios in IoV pose challenges in management and monitoring. One possible streamlined solution is flow-based monitoring which has been widely used from Local Area Network to backbone network. In this paper, we compare and summarize the existing flow-based monitoring methods and their possible use cases in IoV. Considering the potential impact on the Quality of Service (QoS) brought by the monitoring mechanisms, performance evaluations are done in a vehicular network defined with multiple nodes with mobility capability to emulate dynamic IoV scenario in Mininet-wifi. The results present that, sFlow and OpenFlow would bring less impact on QoS as options for IoV network monitoring. The summary and results in this paper would provide inspirations for efficient data monitoring and acquisition in big data-driven IoV.