Correlation Analysis for the Prediction of QoS in V2V Networks

Abstract

Vehicle-to-Vehicle (V2V) communication is an essential component of the Intelligent Transportation System (ITS), which enables realtime traffic data sharing and collective awareness among vehicles and promotes a safer, more effective, and environmentally friendly road traffic environment. One of the main prerequisites for a robust and reliable V2V application minimizing crashes, easing traffic, and reducing traffic congestion is an error-free prediction of the underlying communication performance. In this paper, we delve into the predictive Quality of Service (pQoS) for V2V communication specifically for IEEE 802.11p networks. We establish the correlations between main Key Performance Indicators (KPIs) affecting the V2V communication quality as well as provide recommendations on how these correlations can be used to develop a robust Quality of Service (QoS) prediction algorithm for forecasting and optimizing the V2V performance.

Publication
In Int’l ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications

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