Vehicular Ad Hoc Networks (VANets) is considered as a technology which can increase safety and convenience of drivers and passenger. Due to channel congestion in high density situation, VANets' safety applications suffer of degradation of performance. In order to improve performance, reliability, and safety over VANets, congestion control should be taken into account. However, congestion control is a challenging task due to the special characteristics of VANets (e.g. high mobility, high rate of topology change, frequently broken rout, and so on). In this paper, DySch and TaSch strategies are proposed. Those strategies assign priorities to the safety and service messages based on the content of messages (static factor), state of network (dynamic factor) and size of messages. DySch and TaSch strategies schedule the messages dynamically and heuristically, respectively. Their performance is investigated using highway and urban scenarios while the average delay, average throughput, number of packet loss, packet loss ratio, and waiting delay in queues are considered. Simulation results show that DySch and TaSch strategies can significantly improve the performance of VANets in comparison to the best conventional strategies. Employing the proposed strategies to control congestion in VANets helps increase reliability and safety by giving higher priority to the safety messages.

In an urban environment, intersections are critical locations in terms of road crashes and number of killed or injured people. Vehicular ad hoc networks (VANETs) can help reduce the traffic collisions at intersections by sending warning messages to the vehicles. However, the performance of VANETs should be enhanced to guarantee delivery of the messages, particularly safety messages to the destination. Data congestion control is an efficient way to decrease packet loss and delay and increase the reliability of VANETs. In this paper, a centralized and localized data congestion control strategy is proposed to control data congestion using roadside units (RSUs) at intersections. The proposed strategy consists of three units for detecting congestion, clustering messages, and controlling data congestion. In this strategy, the channel usage level is measured to detect data congestion in the channels. The messages are gathered, filtered, and then clustered by machine learning algorithms. K-means algorithm clusters the messages based on message size, validity of messages, and type of messages. The data congestion control unit determines appropriate values of transmission range and rate, contention window size, and arbitration interframe spacing for each cluster. Finally, RSUs at the intersections send the determined communication parameters to the vehicles stopped before the red traffic lights to reduce communication collisions. Simulation results show that the proposed strategy significantly improves the delay, throughput, and packet loss ratio in comparison with other congestion control strategies using the proposed congestion control strategy.

To provide reliable communications in Vehicular Ad hoc Networks (VANets), it is vital to take into account Quality of Services (QoS). Delay and packet loss are two main QoS parameters considered by congestion control strategies. In this paper, a Multi-Objective Tabu Search (MOTabu) strategy is proposed to control congestion in VANets. The proposed strategy is dynamic and distributed; it consists of two components: congestion detection and congestion control. In the congestion detection component, congestion situation is detected by measuring the channel usage level. In congestion control component, a MOTabu algorithm is used to tune transmission range and rate for both safety and non-safety massages by minimizing delay and jitter. The performance of the proposed strategy is then evaluated with highway and urban scenarios using five performance metrics including the number of packet loss, packet loss ratio, number of retransmissions, average delay, and throughput. Simulation results show that MOTabu strategy significantly outperforms in comparison with other strategies like CSMA/CA, D-FPAV, CABS, and so on. Conducting congestion control using our strategy can help provide more reliable environments in VANets.

In VANET, various limitations such as high mobility, high rate of topology changes, limitation of bandwidth, etc, play a significant role for reducing performance in these networks. Qualities of Service policies have been used to improve the performance of VANET. One of the significant parameters in Quality of Service is Congestion Control. The congestion control is used to ensure safe and reliable communication architecture. Three types of strategies are available for congestion control which consists of transmission power control, packet transmission frequently control and packet duration. Heuristic techniques can be used to define heuristic rules and finding feasible and good enough solution to some problems in reasonable time. According to heuristic's benefits, we are motivated to use these techniques in congestion control to generate efficient VANET. This work is aimed to improve congestion control with heuristic techniques to reduce the traffic communication channels while considering reliability requirements of applications in VANETs. The simulation results have demonstrated that meta-heuristic techniques features significantly better performance in terms of packet loss, throughput and delay compared with other congestion control algorithm within VANETs.