Congestion control in vehicular adhoc network: A survey

Vehicular adhoc network (VANET) has a significant potential in reducing traffic congestion to provide a stress-free and safer platform for road drivers to travel on the road. However, the current VANET is vulnerable to several challenges which need to be overcome. Congestion control is considered as one of the main challenges in VANET due to the high dynamic topology characteristic. Reliable congestion control (CC) are necessary to provide effectient dissemination of time-critical safety messages in VANET applications; safety and non-safety applications. In this paper, we present the overview on VANET, its application and challenges. We also discuss on the congestion control and provide a brief survey on the congestion control algorithms such as vehicular cloud computing, multiplicative rate decreasing algorithm, multi-objective Tabu search, D-FPAV algorithm and beaconing strategies which have been proposed in order to provide better solutions towards achieving a successful Smart Tranporation System

Improving Performance of Opportunistic Routing Protocol using Fuzzy Logic for Vehicular Ad-hoc Networks in Highways

Vehicular ad hoc networks are an emerging technology with an extensive capability in various applications including vehicles safety, traffic management and intelligent transportation systems. Considering the high mobility of vehicles and their inhomogeneous distributions, designing an efficient routing protocol seems necessary. Given the fact that a road is crowded at some sections and is not crowded at the others, the routing protocol should be able to dynamically make decisions. On the other hand, VANET networks environment is vulnerable at the time of data transmission. Broadcast routing, similar to opportunistic routing, could offer better efficiency compared to other protocols. In this paper, a fuzzy logic opportunistic routing (FLOR) protocol is presented in which the packet rebroadcasting decision-making process is carried out through the fuzzy logic system along with three input parameters of packet advancement, local density, and the number of duplicated delivered packets. The rebroadcasting procedures use the value of these parameters as inputs to the fuzzy logic system to resolve the issue of multicasting, considering the crowded and sparse zones. NS-2 simulator is used for evaluating the performance of the proposed FLOR protocol in terms of packet delivery ratio, the end-to-end delay, and the network throughput compared with the existing protocols such as: FLOODING, P-PERSISTENCE and FUZZBR. The performance comparison also emphasizes on effective utilization of the resources. Simulations on highway environment show that the proposed protocol has a better QoS efficiency compared to the above published methods in the literature

Survey on Congestion Detection and Control in Connected Vehicles

The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications

A comprehensive survey on congestion control techniques and the research challenges on VANET

The nature of vehicular mobility and high speed of vehicular ad hoc network (VANET) with dynamic change in the network topology let the vehicular remain as one of the most challenging problems in vehicular-to-vehicular (V2V) communications. Information dissemination is the major problem in VANET with a fixed bandwidth which is causing congestion on the resources, such as channels and affects the performance of the important application, especially when the emergency or secure transmission of messages is exchanged between the vehicles-to-vehicles communication. To mitigate these problems and introduce a safe vehicular environment in urban and highway, congestion detection and control has been considered and with various strategies and techniques which is take the attention of researchers in VANET. In our survey we mentioned recent techniques and approaches which is used in congestion detection and control and applied different matrices and parameters which is used to evaluate these approaches. In addition, the study also explained the limitation and problems that face the current congestion detection and control schemes, finally we present various solution approach and future expectations in vehicular communication

Congestion Control in Vehicular Ad Hoc Networks

RÉSUMÉ Les réseaux Véhiculaires ad hoc (VANets) sont conçus pour permettre des communications sans fil fiables entre les nœuds mobiles à haute vitesse. Afin d'améliorer la performance des applications dans ce type de réseaux et garantir un environnement sûr et confortable pour ses utilisateurs, la Qualité de Service (QoS) doit être supportée dans ces réseaux. Le délai ainsi que les pertes de paquets sont deux principaux indicateurs de QoS qui augmentent de manière significative en raison de la congestion dans les réseaux. En effet, la congestion du réseau entraîne une saturation des canaux ainsi qu’une augmentation des collisions de paquets dans les canaux. Par conséquent, elle doit être contrôlée pour réduire les pertes de paquets ainsi que le délai, et améliorer les performances des réseaux véhiculaires. Le contrôle de congestion dans les réseaux VANets est une tâche difficile en raison des caractéristiques spécifiques des VANets, telles que la grande mobilité des nœuds à haute vitesse, le taux élevé de changement de topologie, etc. Le contrôle de congestion dans les réseaux VANets peut être effectué en ayant recours à une stratégie qui utilise l'un des paramètres suivants : le taux de transmission, la puissance de transmission, la priorisation et l’ordonnancement, ainsi que les stratégies hybrides. Les stratégies de contrôle de congestion dans les réseaux VANets doivent faire face à quelques défis tels que l'utilisation inéquitable des ressources, la surcharge de communication, le délai de transmission élevé, et l'utilisation inefficace de la bande passante, etc. Par conséquent, il est nécessaire de développer de nouvelles approches pour faire face à ces défis et améliorer la performance des réseaux VANets. Dans cette thèse, dans un premier temps, une stratégie de contrôle de congestion en boucle fermée est développée. Cette stratégie est une méthode de contrôle de congestion dynamique et distribuée qui détecte la congestion en mesurant le niveau d'utilisation du canal. Ensuite, la congestion est contrôlée en ajustant la portée et le taux de transmission qui ont un impact considérable sur la saturation du canal. Ajuster la portée et le taux de transmission au sein des VANets est un problème NP-difficile en raison de la grande complexité de la détermination des valeurs appropriées pour ces paramètres. Considérant les avantages de la méthode de recherche Tabou et son adaptabilité au problème, une méthode de recherche multi-objective est utilisée pour trouver une portée et un taux de transmission dans un délai raisonnable. Le délai et la gigue, fonctions multi-objectifs de l'algorithme Tabou, sont minimisés dans l'algorithme proposé. Par la suite, deux stratégies de contrôle de congestion en boucle ouverte sont proposées afin de réduire la congestion dans les canaux en utilisant la priorisation et l'ordonnancement des messages. Ces stratégies définissent la priorité pour chaque message en considérant son type de contenu (par exemple les messages d'urgence, de beacon, et de service), la taille des messages, et l’état du réseau (par exemple, les métriques de la vélocité, la direction, l'utilité, la distance, et la validité). L'ordonnancement des messages est effectué sur la base des priorités définies. De plus, comme seconde technique d'ordonnancement, une méthode de recherche Tabou est employée pour planifier les files d'attente de contrôle et de service des canaux de transmission dans un délai raisonnable. A cet effet, le délai et la gigue lors de l'acheminement des messages sont minimisés. Enfin, une stratégie localisée et centralisée qui utilise les ensembles RSU fixés aux intersections pour détecter et contrôler de la congestion est proposée. Cette stratégie regroupe tous les messages transférés entre les véhicules qui se sont arrêtés à une lumière de signalisation en utilisant les algorithmes de Machine Learning. Dans cette stratégie, un algorithme de k-means est utilisé pour regrouper les messages en fonction de leurs caractéristiques (par exemple la taille des messages, la validité des messages, et le type de messages, etc.). Les paramètres de communication, y compris le portée et le taux de transmission, la taille de la fenêtre de contention, et le paramètre AIFS (Arbitration Inter-Frame Spacing) sont déterminés pour chaque grappe de messages en vue de minimiser le délai de livraison. Ensuite, les paramètres de communication déterminés sont envoyés aux véhicules par les RSUs, et les véhicules opèrent en fonction de ces paramètres pour le transfert des messages. Les performances des trois stratégies proposées ont été évaluées en simulant des scénarios dans les autoroutes et la circulation urbaine avec les simulateurs NS2 et SUMO. Des comparaisons ont aussi été faites entre les résultats obtenus à partir des stratégies proposées et les stratégies de contrôle de congestion communément utilisées. Les résultats révèlent qu’avec les stratégies de contrôle de congestion proposées, le débit du réseau augmente et le taux de perte de paquets ainsi que de délai diminuent de manière significative en comparaison aux autres stratégies. Par conséquent, l'application des méthodes proposées aide à améliorer la performance, la sureté et la fiabilité des VANets.----------ABSTRACT Vehicular Ad hoc Networks (VANets) are designed to provide reliable wireless communications between high-speed mobile nodes. In order to improve the performance of VANets’ applications, and make a safe and comfort environment for VANets’ users, Quality of Service (QoS) should be supported in these networks. The delay and packet losses are two main indicators of QoS that dramatically increase due to the congestion occurrence in the networks. Indeed, due to congestion occurrence, the channels are saturated and the packet collisions increase in the channels. Therefore, the congestion should be controlled to decrease the packet losses and delay, and to increase the performance of VANets. Congestion control in VANets is a challenging task due to the specific characteristics of VANets such as high mobility of the nodes with high speed, and high rate of topology changes, and so on. Congestion control in VANets can be carried out using the strategies that can be classified into rate-based, power-based, CSMA/CA-based, prioritizing and scheduling-based, and hybrid strategies. The congestion control strategies in VANets face to some challenges such as unfair resources usage, communication overhead, high transmission delay, and inefficient bandwidth utilization, and so on. Therefore, it is required to develop new strategies to cope with these challenges and improve the performance of VANets. In this dissertation, first, a closed-loop congestion control strategy is developed. This strategy is a dynamic and distributed congestion control strategy that detects the congestion by measuring the channel usage level. Then, the congestion is controlled by tuning the transmission range and rate that considerably impact on the channel saturation. Tuning the transmission range and rate in VANets is an NP-hard problem due to the high complexity of determining the proper values for these parameters in vehicular networks. Considering the benefits of Tabu search algorithm and its adaptability with the problem, a multi-objective Tabu search algorithm is used for tuning transmission range and rate in reasonable time. In the proposed algorithm, the delay and jitter are minimized as the objective functions of multi-objective Tabu Search algorithm. Second, two open-loop congestion control strategies are proposed that prevent the congestion occurrence in the channels using the prioritizing and scheduling the messages. These strategies define the priority for each message by considering the content of messages (i.e. types of the messages for example emergency, beacon, and service messages), size of messages, and state of the networks (e.g. velocity, direction, usefulness, distance and validity metrics). The scheduling of the messages is conducted based on the defined priorities. In addition, as the second scheduling technique, a Tabu Search algorithm is employed to schedule the control and service channel queues in a reasonable time. For this purpose, the delay and jitter of messages delivery are minimized. Finally, a localized and centralized strategy is proposed that uses RSUs set at intersections for detecting and controlling the congestion. These strategy clusters all the messages that transferred between the vehicles stopped before the red traffic light using Machine Learning algorithms. In this strategy, a K-means learning algorithm is used for clustering the messages based on their features (e.g. size of messages, validity of messages, and type of messages, and so on). The communication parameters including the transmission range and rate, contention window size, and Arbitration Inter-Frame Spacing (AIFS) are determined for each messages cluter based on the minimized delivery delay. Then, the determined communication parameters are sent to the vehicles by RSUs, and the vehicles operate based on these parameters for transferring the messages. The performances of three proposed strategies were evaluated by simulating the highway and urban scenarios in NS2 and SUMO simulators. Comparisons were also made between the results obtained from the proposed strategies and the common used congestion control strategies. The results reveal that using the proposed congestion control strategies, the throughput, packet loss ratio and delay are significantly improved as compared to the other strategies. Therefore, applications of the proposed strategies help improve the performance, safety, and reliability of VANets