Managing Congestion in Vehicular Networks Using Tabu Search

© 2018, Springer Nature Switzerland AG. In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control congestion. A particular case is applicable to Vehicular Ad-hoc Networks, which are known with unbalanced resource utilisation, communication overheads, high transmission delay and least transmission capacity. This paper aims to minimise the delay and jitter for enhancing the Quality of Service (QoS) in Vehicular Adhoc Networks (VANET) using tabu search algorithm with multi-channel allocation capability. We proposed a scheme that prioritises each message considering the basis of message type or its substances, such as crisis, reference point, and administration oriented etc., and uses tabu search for scheduling the transmission of queued messages in order to enhance the efficiency, security, and durability of VANET. A comprehensive simulation is conducted to validate the proposed scheme and to evaluate the performances in comparison with other state-of-the-art approaches

Reliable and efficient data dissemination schemein VANET: a review

Vehicular ad-hoc network (VANET), identified as a mobile ad hoc network MANETs with several added constraints. Basically, in VANETs, the network is established on the fly based on the availability of vehicles on roads and supporting infrastructures along the roads, such as base stations. Vehicles and road-side infrastructures are required to provide communication facilities, particularly when enough vehicles are not available on the roads for effective communication. VANETs are crucial for providing a wide range of safety and non-safety applications to road users. However, the specific fundamental problem in VANET is the challenge of creating effective communication between two fast-moving vehicles. Therefore, message routing is an issue for many safety and non-safety of VANETs applications. The challenge in designing a robust but reliable message dissemination technique is primarily due to the stringent QoS requirements of the VANETs safety applications. This paper investigated various methods and conducted literature on an idea to develop a model for efficient and reliable message dissemination routing techniques in VANET

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

Optimization of vehicular networks in smart cities: from agile optimization to learnheuristics and simheuristics

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.Peer ReviewedPostprint (published version

Survey on decentralized congestion control methods for vehicular communication

Vehicular communications have grown in interest over the years and are nowadays recognized as a pillar for the Intelligent Transportation Systems (ITSs) in order to ensure an efficient management of the road traffic and to achieve a reduction in the number of traffic accidents. To support the safety applications, both the ETSI ITS-G5 and IEEE 1609 standard families require each vehicle to deliver periodic awareness messages throughout the neighborhood. As the vehicles density grows, the scenario dynamics may require a high message exchange that can easily lead to a radio channel congestion issue and then to a degradation on safety critical services. ETSI has defined a Decentralized Congestion Control (DCC) mechanism to mitigate the channel congestion acting on the transmission parameters (i.e., message rate, transmit power and data-rate) with performances that vary according to the specific algorithm. In this paper, a review of the DCC standardization activities is proposed as well as an analysis of the existing methods and algorithms for the congestion mitigation. Also, some applied machine learning techniques for DCC are addressed

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

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

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

Survey and Review on Various Topology and Geographical based Routing Protocol Parameters to Ensure the QOS Parameters of VANET

Vehicular Ad Hoc Network (VANET) is a type of wireless network that allows communication between vehicles and infrastructure. One of the critical considerations in VANET is Quality of Service (QoS) parameters, which determine the network's performance. The effective management of QoS parameters is essential for VANET's reliable and efficient operation. In this research paper, we aim to explore topology-based and geographical-based routing protocol parameters to ensure QoS parameters in VANET. The former uses the network topology to make routing decisions, while the latter uses the location information of vehicles.  We will first provide an overview of VANET and QoS parameters. Then, we will delve into the key parameters of topology-based and geographical-based routing protocols and how they affect QoS. We will also survey and review the existing routing protocols and parameter values used in these protocols. The findings of this research paper will provide insights into the effective management of QoS parameters in VANET and contribute to the development of more efficient routing protocols

Adaptive scheduled partitioning technique for reliable emergency message broadcasting in VANET for intelligent transportation systems

This paper aims to enable accurate and reliable emergency message broadcast in Vehicular Ad hoc Network (VANET). The VANET is the most common topology used in Intelligent Transportation Systems (ITS), where changes in standard topology due to the mobility of nodes create challenges in broadcasting the emergency message and efficient data delivery in both highway and urban scenarios. The main problems in urban scenarios are channel contention, message redundancy and road structure. To obtain information, broadcast protocols for VANET typically use beacon messages, which are distributed among the vehicles. When multiple vehicles transmit messages at the same time, a broadcast storm occurs and vehicles experience message delivery failure. To address this problem, Adaptive Scheduled Partitioning and Broadcasting Technique (ASPBT) for emergency message broadcast and beacon retransmissions for message reliability were proposed. This protocol dynamically modifies several partitions and beacon periodicity to reduce the number of retransmissions. Later, the partition size is determined by estimating the network transmission density of each partition schedule via the Black Widow Optimization (BWO) algorithm is proposed. The simulation is carried out with different network densities at the vehicle speed of 110 km/h, a direct path length of 12 km under a four-way direction path and performance analysis was performed