Channel-Aware Congestion Control in Vehicular Cyber-Physical Systems

Abstract

In vehicular cyber-physical systems, cars are connected to create a mobile network called a vehicular ad hoc network (VANET) to perform various functions, including improved awareness of the surrounding environment. Moving vehicles continually broadcast beacon signals containing information such as position, heading, acceleration, steering angle, vehicle size, and accident notification. However, channel congestion in dense traffic conditions adversely affects network performance. To resolve congestion in VANETs, several works in the literature have studied congestion control. However, they have considered packet loss only as an indication of channel congestion regardless of channel condition. In this paper, we present a channel-aware congestion control algorithm (CACC) that controls the transmission power and data rate. We take into account the received signal strength (RSS) when diagnosing packet loss to determine channel conditions, such as severe fading or channel congestion. In the case of severe fading, we decrease the data rate for a more robust modulation and coding scheme. Additionally, we adjust the transmission power to maintain a desirable packet error rate. Our simulation results show that CACC significantly outperforms other distributed congestion control algorithms by reducing the packet loss rate and increasing the packet delivery ratio. INDEX TERMS Congestion control, channel-aware protocol, mobile cyber-physical systems, packet loss, vehicular ad hoc networks.

A Centralized and Dynamic Network Congestion Classification Approach for Heterogeneous Vehicular Networks

“…Congestion in the network leads to a reduction in the data delivery ratio. This metric is considered in vehicular network congestion-related work to detect congestion [11], [28]. However, packet loss could also accrue due to weak signals.…”

“…Thus, this method provides tolerable congestion management approach that can define different congestion warning intervals over time and is based on the network's situation. For example, if the network management unit assigned −96.26 dBm for RSS th , 0.4 as a value for DDR minth and 0.6 as a value for DDR maxth then it is a warning state while the data is flowing, when DDR ∈ [0.4, 0.6] and the value of RSS is more than −96.26 dBm [28].…”

“…DCC (used in ETSI) is based on changing the value of the data transmission rate and transmission power [4], [31], [38]. Additionally, most of the proposed congestion controls in WAVE standard are based on adapting the transmission power and data transmission rate [28], [39]- [41]. Therefore, in each run, we changed the value of v, dr, tp DSRC , tp LT E and b according to Table 1, and we calculated the values of DDR and RSS.…”

“…In [28], the authors proposed an RSS cutoff value for V2V communication, in which if the RSS is higher than the cutoff value, then the packet loss is due to network congestion. They provide simulation results and technical discussions to support this issue.…”

On the Potential of V2X Message Compression for Vehicular Networks

“…These protocols normally adapt the communication parameters, e.g. the message rate [1] [2], the transmission power [3] [4], or the data rate [5] [6] to control the load. These solutions reduce the channel load at the expense of modifying the amount of information exchanged, the communication range or the protection against transmission errors [7].…”